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image</title> <meta name="description" content="Search results for: thermal image"> <meta name="keywords" content="thermal image"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler 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id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="thermal image"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 6233</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: thermal image</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6233</span> Thermal Image Segmentation Method for Stratification of Freezing Temperatures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Azam%20Fazelpour">Azam Fazelpour</a>, <a href="https://publications.waset.org/abstracts/search?q=Saeed%20R.%20Dehghani"> Saeed R. Dehghani</a>, <a href="https://publications.waset.org/abstracts/search?q=Vlastimil%20Masek"> Vlastimil Masek</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuri%20S.%20Muzychka"> Yuri S. Muzychka</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The study uses an image analysis technique employing thermal imaging to measure the percentage of areas with various temperatures on a freezing surface. An image segmentation method using threshold values is applied to a sequence of image recording the freezing process. The phenomenon is transient and temperatures vary fast to reach the freezing point and complete the freezing process. Freezing salt water is subjected to the salt rejection that makes the freezing point dynamic and dependent on the salinity at the phase interface. For a specific area of freezing, nucleation starts from one side and end to another side, which causes a dynamic and transient temperature in that area. Thermal cameras are able to reveal a difference in temperature due to their sensitivity to infrared radiance. Using Experimental setup, a video is recorded by a thermal camera to monitor radiance and temperatures during the freezing process. Image processing techniques are applied to all frames to detect and classify temperatures on the surface. Image processing segmentation method is used to find contours with same temperatures on the icing surface. Each segment is obtained using the temperature range appeared in the image and correspond pixel values in the image. Using the contours extracted from image and camera parameters, stratified areas with different temperatures are calculated. To observe temperature contours on the icing surface using the thermal camera, the salt water sample is dropped on a cold surface with the temperature of -20掳C. A thermal video is recorded for 2 minutes to observe the temperature field. Examining the results obtained by the method and the experimental observations verifies the accuracy and applicability of the method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ice%20contour%20boundary" title="ice contour boundary">ice contour boundary</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20segmentation" title=" image segmentation"> image segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=salt%20ice" title=" salt ice"> salt ice</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20image" title=" thermal image"> thermal image</a> </p> <a href="https://publications.waset.org/abstracts/65771/thermal-image-segmentation-method-for-stratification-of-freezing-temperatures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65771.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">320</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6232</span> Multi-Sensor Image Fusion for Visible and Infrared Thermal Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amit%20Kumar%20Happy">Amit Kumar Happy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper is motivated by the importance of multi-sensor image fusion with a specific focus on infrared (IR) and visual image (VI) fusion for various applications, including military reconnaissance. Image fusion can be defined as the process of combining two or more source images into a single composite image with extended information content that improves visual perception or feature extraction. These images can be from different modalities like visible camera & IR thermal imager. While visible images are captured by reflected radiations in the visible spectrum, the thermal images are formed from thermal radiation (infrared) that may be reflected or self-emitted. A digital color camera captures the visible source image, and a thermal infrared camera acquires the thermal source image. In this paper, some image fusion algorithms based upon multi-scale transform (MST) and region-based selection rule with consistency verification have been proposed and presented. This research includes the implementation of the proposed image fusion algorithm in MATLAB along with a comparative analysis to decide the optimum number of levels for MST and the coefficient fusion rule. The results are presented, and several commonly used evaluation metrics are used to assess the suggested method's validity. Experiments show that the proposed approach is capable of producing good fusion results. While deploying our image fusion algorithm approaches, we observe several challenges from the popular image fusion methods. While high computational cost and complex processing steps of image fusion algorithms provide accurate fused results, they also make it hard to become deployed in systems and applications that require a real-time operation, high flexibility, and low computation ability. So, the methods presented in this paper offer good results with minimum time complexity. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20fusion" title="image fusion">image fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=IR%20thermal%20imager" title=" IR thermal imager"> IR thermal imager</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-sensor" title=" multi-sensor"> multi-sensor</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-scale%20transform" title=" multi-scale transform"> multi-scale transform</a> </p> <a href="https://publications.waset.org/abstracts/138086/multi-sensor-image-fusion-for-visible-and-infrared-thermal-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/138086.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">115</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6231</span> Monocular Depth Estimation Benchmarking with Thermal Dataset</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Akyar">Ali Akyar</a>, <a href="https://publications.waset.org/abstracts/search?q=Osman%20Serdar%20Gedik"> Osman Serdar Gedik</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Depth estimation is a challenging computer vision task that involves estimating the distance between objects in a scene and the camera. It predicts how far each pixel in the 2D image is from the capturing point. There are some important Monocular Depth Estimation (MDE) studies that are based on Vision Transformers (ViT). We benchmark three major studies. The first work aims to build a simple and powerful foundation model that deals with any images under any condition. The second work proposes a method by mixing multiple datasets during training and a robust training objective. The third work combines generalization performance and state-of-the-art results on specific datasets. Although there are studies with thermal images too, we wanted to benchmark these three non-thermal, state-of-the-art studies with a hybrid image dataset which is taken by Multi-Spectral Dynamic Imaging (MSX) technology. MSX technology produces detailed thermal images by bringing together the thermal and visual spectrums. Using this technology, our dataset images are not blur and poorly detailed as the normal thermal images. On the other hand, they are not taken at the perfect light conditions as RGB images. We compared three methods under test with our thermal dataset which was not done before. Additionally, we propose an image enhancement deep learning model for thermal data. This model helps extract the features required for monocular depth estimation. The experimental results demonstrate that, after using our proposed model, the performance of these three methods under test increased significantly for thermal image depth prediction. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=monocular%20depth%20estimation" title="monocular depth estimation">monocular depth estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20dataset" title=" thermal dataset"> thermal dataset</a>, <a href="https://publications.waset.org/abstracts/search?q=benchmarking" title=" benchmarking"> benchmarking</a>, <a href="https://publications.waset.org/abstracts/search?q=vision%20transformers" title=" vision transformers"> vision transformers</a> </p> <a href="https://publications.waset.org/abstracts/186398/monocular-depth-estimation-benchmarking-with-thermal-dataset" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186398.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">32</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6230</span> Depth Estimation in DNN Using Stereo Thermal Image Pairs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahmet%20Faruk%20Akyuz">Ahmet Faruk Akyuz</a>, <a href="https://publications.waset.org/abstracts/search?q=Hasan%20Sakir%20Bilge">Hasan Sakir Bilge</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Depth estimation using stereo images is a challenging problem in computer vision. Many different studies have been carried out to solve this problem. With advancing machine learning, tackling this problem is often done with neural network-based solutions. The images used in these studies are mostly in the visible spectrum. However, the need to use the Infrared (IR) spectrum for depth estimation has emerged because it gives better results than visible spectra in some conditions. At this point, we recommend using thermal-thermal (IR) image pairs for depth estimation. In this study, we used two well-known networks (PSMNet, FADNet) with minor modifications to demonstrate the viability of this idea. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=thermal%20stereo%20matching" title="thermal stereo matching">thermal stereo matching</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20neural%20networks" title="deep neural networks">deep neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=CNN" title="CNN">CNN</a>, <a href="https://publications.waset.org/abstracts/search?q=Depth%20estimation" title="Depth estimation">Depth estimation</a> </p> <a href="https://publications.waset.org/abstracts/140133/depth-estimation-in-dnn-using-stereo-thermal-image-pairs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/140133.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">279</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6229</span> The Influence of Fiber Volume Fraction on Thermal Conductivity of Pultruded Profile</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=V.%20Luk%C3%A1%C5%A1ov%C3%A1">V. Luk谩拧ov谩</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Peukert"> P. Peukert</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20Votrubec"> V. Votrubec</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Thermal conductivity in the x, y and z-directions was measured on a pultruded profile that was manufactured by the technology of pulling from glass fibers and a polyester matrix. The results of measurements of thermal conductivity showed considerable variability in different directions. The caused variability in thermal conductivity was expected due fraction variations. The cross-section of the pultruded profile was scanned. An image analysis illustrated an uneven distribution of the fibers and the matrix in the cross-section. The distribution of these inequalities was processed into a Voronoi diagram in the observed area of the pultruded profile cross-section. In order to verify whether the variation of the fiber volume fraction in the pultruded profile can affect its thermal conductivity, the numerical simulations in the ANSYS Fluent were performed. The simulation was based on the geometry reconstructed from image analysis. The aim is to quantify thermal conductivity numerically. Above all, images with different volume fractions were chosen. The results of the measured thermal conductivity were compared with the calculated thermal conductivity. The evaluated data proved a strong correlation between volume fraction and thermal conductivity of the pultruded profile. Based on presented results, a modification of production technology may be proposed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=pultrusion%20profile" title="pultrusion profile">pultrusion profile</a>, <a href="https://publications.waset.org/abstracts/search?q=volume%20fraction" title=" volume fraction"> volume fraction</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20conductivity" title=" thermal conductivity"> thermal conductivity</a>, <a href="https://publications.waset.org/abstracts/search?q=numerical%20simulation" title=" numerical simulation"> numerical simulation</a> </p> <a href="https://publications.waset.org/abstracts/52483/the-influence-of-fiber-volume-fraction-on-thermal-conductivity-of-pultruded-profile" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52483.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">346</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6228</span> Best Timing for Capturing Satellite Thermal Images, Asphalt, and Concrete Objects</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Toufic%20Abd%20El-Latif%20Sadek">Toufic Abd El-Latif Sadek</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The asphalt object represents the asphalted areas like roads, and the concrete object represents the concrete areas like concrete buildings. The efficient extraction of asphalt and concrete objects from one satellite thermal image occurred at a specific time, by preventing the gaps in times which give the close and same brightness values between asphalt and concrete, and among other objects. So that to achieve efficient extraction and then better analysis. Seven sample objects were used un this study, asphalt, concrete, metal, rock, dry soil, vegetation, and water. It has been found that, the best timing for capturing satellite thermal images to extract the two objects asphalt and concrete from one satellite thermal image, saving time and money, occurred at a specific time in different months. A table is deduced shows the optimal timing for capturing satellite thermal images to extract effectively these two objects. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=asphalt" title="asphalt">asphalt</a>, <a href="https://publications.waset.org/abstracts/search?q=concrete" title=" concrete"> concrete</a>, <a href="https://publications.waset.org/abstracts/search?q=satellite%20thermal%20images" title=" satellite thermal images"> satellite thermal images</a>, <a href="https://publications.waset.org/abstracts/search?q=timing" title=" timing"> timing</a> </p> <a href="https://publications.waset.org/abstracts/51827/best-timing-for-capturing-satellite-thermal-images-asphalt-and-concrete-objects" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51827.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">322</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6227</span> Gaussian Probability Density for Forest Fire Detection Using Satellite Imagery</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Benkraouda">S. Benkraouda</a>, <a href="https://publications.waset.org/abstracts/search?q=Z.%20Djelloul-Khedda"> Z. Djelloul-Khedda</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Yagoubi"> B. Yagoubi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> we present a method for early detection of forest fires from a thermal infrared satellite image, using the image matrix of the probability of belonging. The principle of the method is to compare a theoretical mathematical model to an experimental model. We considered that each line of the image matrix, as an embodiment of a non-stationary random process. Since the distribution of pixels in the satellite image is statistically dependent, we divided these lines into small stationary and ergodic intervals to characterize the image by an adequate mathematical model. A standard deviation was chosen to generate random variables, so each interval behaves naturally like white Gaussian noise. The latter has been selected as the mathematical model that represents a set of very majority pixels, which we can be considered as the image background. Before modeling the image, we made a few pretreatments, then the parameters of the theoretical Gaussian model were extracted from the modeled image, these settings will be used to calculate the probability of each interval of the modeled image to belong to the theoretical Gaussian model. The high intensities pixels are regarded as foreign elements to it, so they will have a low probability, and the pixels that belong to the background image will have a high probability. Finally, we did present the reverse of the matrix of probabilities of these intervals for a better fire detection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=forest%20fire" title="forest fire">forest fire</a>, <a href="https://publications.waset.org/abstracts/search?q=forest%20fire%20detection" title=" forest fire detection"> forest fire detection</a>, <a href="https://publications.waset.org/abstracts/search?q=satellite%20image" title=" satellite image"> satellite image</a>, <a href="https://publications.waset.org/abstracts/search?q=normal%20distribution" title=" normal distribution"> normal distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=theoretical%20gaussian%20model" title=" theoretical gaussian model"> theoretical gaussian model</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20infrared%20matrix%20image" title=" thermal infrared matrix image"> thermal infrared matrix image</a> </p> <a href="https://publications.waset.org/abstracts/118320/gaussian-probability-density-for-forest-fire-detection-using-satellite-imagery" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/118320.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">142</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6226</span> Temperature Contour Detection of Salt Ice Using Color Thermal Image Segmentation Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Azam%20Fazelpour">Azam Fazelpour</a>, <a href="https://publications.waset.org/abstracts/search?q=Saeed%20Reza%20Dehghani"> Saeed Reza Dehghani</a>, <a href="https://publications.waset.org/abstracts/search?q=Vlastimil%20Masek"> Vlastimil Masek</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuri%20S.%20Muzychka"> Yuri S. Muzychka</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The study uses a novel image analysis based on thermal imaging to detect temperature contours created on salt ice surface during transient phenomena. Thermal cameras detect objects by using their emissivities and IR radiance. The ice surface temperature is not uniform during transient processes. The temperature starts to increase from the boundary of ice towards the center of that. Thermal cameras are able to report temperature changes on the ice surface at every individual moment. Various contours, which show different temperature areas, appear on the ice surface picture captured by a thermal camera. Identifying the exact boundary of these contours is valuable to facilitate ice surface temperature analysis. Image processing techniques are used to extract each contour area precisely. In this study, several pictures are recorded while the temperature is increasing throughout the ice surface. Some pictures are selected to be processed by a specific time interval. An image segmentation method is applied to images to determine the contour areas. Color thermal images are used to exploit the main information. Red, green and blue elements of color images are investigated to find the best contour boundaries. The algorithms of image enhancement and noise removal are applied to images to obtain a high contrast and clear image. A novel edge detection algorithm based on differences in the color of the pixels is established to determine contour boundaries. In this method, the edges of the contours are obtained according to properties of red, blue and green image elements. The color image elements are assessed considering their information. Useful elements proceed to process and useless elements are removed from the process to reduce the consuming time. Neighbor pixels with close intensities are assigned in one contour and differences in intensities determine boundaries. The results are then verified by conducting experimental tests. An experimental setup is performed using ice samples and a thermal camera. To observe the created ice contour by the thermal camera, the samples, which are initially at -20掳 C, are contacted with a warmer surface. Pictures are captured for 20 seconds. The method is applied to five images ,which are captured at the time intervals of 5 seconds. The study shows the green image element carries no useful information; therefore, the boundary detection method is applied on red and blue image elements. In this case study, the results indicate that proposed algorithm shows the boundaries more effective than other edges detection methods such as Sobel and Canny. Comparison between the contour detection in this method and temperature analysis, which states real boundaries, shows a good agreement. This color image edge detection method is applicable to other similar cases according to their image properties. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=color%20image%20processing" title="color image processing">color image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=edge%20detection" title=" edge detection"> edge detection</a>, <a href="https://publications.waset.org/abstracts/search?q=ice%20contour%20boundary" title=" ice contour boundary"> ice contour boundary</a>, <a href="https://publications.waset.org/abstracts/search?q=salt%20ice" title=" salt ice"> salt ice</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20image" title=" thermal image"> thermal image</a> </p> <a href="https://publications.waset.org/abstracts/61867/temperature-contour-detection-of-salt-ice-using-color-thermal-image-segmentation-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/61867.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">314</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6225</span> The Use of Thermal Infrared Wavelengths to Determine the Volcanic Soils</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Levent%20Basayigit">Levent Basayigit</a>, <a href="https://publications.waset.org/abstracts/search?q=Mert%20Dedeoglu"> Mert Dedeoglu</a>, <a href="https://publications.waset.org/abstracts/search?q=Fadime%20Ozogul"> Fadime Ozogul</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, an application was carried out to determine the Volcanic Soils by using remote sensing.  The study area was located on the Golcuk formation in Isparta-Turkey. The thermal bands of Landsat 7 image were used for processing. The implementation of the climate model that was based on the water index was used in ERDAS Imagine software together with pixel based image classification. Soil Moisture Index (SMI) was modeled by using the surface temperature (Ts) which was obtained from thermal bands and vegetation index (NDVI) derived from Landsat 7. Surface moisture values were grouped and classified by using scoring system. Thematic layers were compared together with the field studies. Consequently, different moisture levels for volcanic soils were indicator for determination and separation. Those thermal wavelengths are preferable bands for separation of volcanic soils using moisture and temperature models. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Landsat%207" title="Landsat 7">Landsat 7</a>, <a href="https://publications.waset.org/abstracts/search?q=soil%20moisture%20index" title=" soil moisture index"> soil moisture index</a>, <a href="https://publications.waset.org/abstracts/search?q=temperature%20models" title=" temperature models"> temperature models</a>, <a href="https://publications.waset.org/abstracts/search?q=volcanic%20soils" title=" volcanic soils"> volcanic soils</a> </p> <a href="https://publications.waset.org/abstracts/68582/the-use-of-thermal-infrared-wavelengths-to-determine-the-volcanic-soils" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68582.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">305</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6224</span> Robust Image Registration Based on an Adaptive Normalized Mutual Information Metric</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Huda%20Algharib">Huda Algharib</a>, <a href="https://publications.waset.org/abstracts/search?q=Amal%20Algharib"> Amal Algharib</a>, <a href="https://publications.waset.org/abstracts/search?q=Hanan%20Algharib"> Hanan Algharib</a>, <a href="https://publications.waset.org/abstracts/search?q=Ali%20Mohammad%20Alqudah"> Ali Mohammad Alqudah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Image registration is an important topic for many imaging systems and computer vision applications. The standard image registration techniques such as Mutual information/ Normalized mutual information -based methods have a limited performance because they do not consider the spatial information or the relationships between the neighbouring pixels or voxels. In addition, the amount of image noise may significantly affect the registration accuracy. Therefore, this paper proposes an efficient method that explicitly considers the relationships between the adjacent pixels, where the gradient information of the reference and scene images is extracted first, and then the cosine similarity of the extracted gradient information is computed and used to improve the accuracy of the standard normalized mutual information measure. Our experimental results on different data types (i.e. CT, MRI and thermal images) show that the proposed method outperforms a number of image registration techniques in terms of the accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20registration" title="image registration">image registration</a>, <a href="https://publications.waset.org/abstracts/search?q=mutual%20information" title=" mutual information"> mutual information</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20gradients" title=" image gradients"> image gradients</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20transformations" title=" image transformations"> image transformations</a> </p> <a href="https://publications.waset.org/abstracts/82815/robust-image-registration-based-on-an-adaptive-normalized-mutual-information-metric" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/82815.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">248</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6223</span> Noninvasive Evaluation of Acupuncture by Measuring Facial Temperature through Thermal Image</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=An%20Guo">An Guo</a>, <a href="https://publications.waset.org/abstracts/search?q=Hieyong%20Jeong"> Hieyong Jeong</a>, <a href="https://publications.waset.org/abstracts/search?q=Tianyi%20Wang"> Tianyi Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Na%20Li"> Na Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuko%20Ohno"> Yuko Ohno</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Acupuncture, known as sensory simulation, has been used to treat various disorders for thousands of years. However, present studies had not addressed approaches for noninvasive measurement in order to evaluate therapeutic effect of acupuncture. The purpose of this study is to propose a noninvasive method to evaluate acupuncture by measuring facial temperature through thermal image. Three human subjects were recruited in this study. Each subject received acupuncture therapy for 30 mins. Acupuncture needles (脴0.16 x 30 mm) were inserted into Baihui point (DU20), Neiguan points (PC6) and Taichong points (LR3), acupuncture needles (脴0.18 x 39 mm) were inserted into Tanzhong point (RN17), Zusanli points (ST36) and Yinlingquan points (SP9). Facial temperature was recorded by an infrared thermometer. Acupuncture therapeutic effect was compared pre- and post-acupuncture. Experiment results demonstrated that facial temperature changed according to acupuncture therapeutic effect. It was concluded that proposed method showed high potential to evaluate acupuncture by noninvasive measurement of facial temperature. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=acupuncture" title="acupuncture">acupuncture</a>, <a href="https://publications.waset.org/abstracts/search?q=facial%20temperature" title=" facial temperature"> facial temperature</a>, <a href="https://publications.waset.org/abstracts/search?q=noninvasive%20evaluation" title=" noninvasive evaluation"> noninvasive evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20image" title=" thermal image"> thermal image</a> </p> <a href="https://publications.waset.org/abstracts/95222/noninvasive-evaluation-of-acupuncture-by-measuring-facial-temperature-through-thermal-image" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95222.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">187</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6222</span> An Intelligent Nondestructive Testing System of Ultrasonic Infrared Thermal Imaging Based on Embedded Linux</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hao%20Mi">Hao Mi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ming%20Yang"> Ming Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Tian-yue%20Yang"> Tian-yue Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ultrasonic infrared nondestructive testing is a kind of testing method with high speed, accuracy and localization. However, there are still some problems, such as the detection requires manual real-time field judgment, the methods of result storage and viewing are still primitive. An intelligent non-destructive detection system based on embedded linux is put forward in this paper. The hardware part of the detection system is based on the ARM (Advanced Reduced Instruction Set Computer Machine) core and an embedded linux system is built to realize image processing and defect detection of thermal images. The CLAHE algorithm and the Butterworth filter are used to process the thermal image, and then the boa server and CGI (Common Gateway Interface) technology are used to transmit the test results to the display terminal through the network for real-time monitoring and remote monitoring. The system also liberates labor and eliminates the obstacle of manual judgment. According to the experiment result, the system provides a convenient and quick solution for industrial non-destructive testing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=remote%20monitoring" title="remote monitoring">remote monitoring</a>, <a href="https://publications.waset.org/abstracts/search?q=non-destructive%20testing" title=" non-destructive testing"> non-destructive testing</a>, <a href="https://publications.waset.org/abstracts/search?q=embedded%20Linux%20system" title=" embedded Linux system"> embedded Linux system</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a> </p> <a href="https://publications.waset.org/abstracts/101979/an-intelligent-nondestructive-testing-system-of-ultrasonic-infrared-thermal-imaging-based-on-embedded-linux" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/101979.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">224</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6221</span> Design and Implementation of Image Super-Resolution for Myocardial Image</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20V.%20Chidananda%20Murthy">M. V. Chidananda Murthy</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Z.%20Kurian"> M. Z. Kurian</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20S.%20Guruprasad"> H. S. Guruprasad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Super-resolution is the technique of intelligently upscaling images, avoiding artifacts or blurring, and deals with the recovery of a high-resolution image from one or more low-resolution images. Single-image super-resolution is a process of obtaining a high-resolution image from a set of low-resolution observations by signal processing. While super-resolution has been demonstrated to improve image quality in scaled down images in the image domain, its effects on the Fourier-based technique remains unknown. Super-resolution substantially improved the spatial resolution of the patient LGE images by sharpening the edges of the heart and the scar. This paper aims at investigating the effects of single image super-resolution on Fourier-based and image based methods of scale-up. In this paper, first, generate a training phase of the low-resolution image and high-resolution image to obtain dictionary. In the test phase, first, generate a patch and then difference of high-resolution image and interpolation image from the low-resolution image. Next simulation of the image is obtained by applying convolution method to the dictionary creation image and patch extracted the image. Finally, super-resolution image is obtained by combining the fused image and difference of high-resolution and interpolated image. Super-resolution reduces image errors and improves the image quality. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20dictionary%20creation" title="image dictionary creation">image dictionary creation</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20super-resolution" title=" image super-resolution"> image super-resolution</a>, <a href="https://publications.waset.org/abstracts/search?q=LGE%20images" title=" LGE images"> LGE images</a>, <a href="https://publications.waset.org/abstracts/search?q=patch%20extraction" title=" patch extraction"> patch extraction</a> </p> <a href="https://publications.waset.org/abstracts/59494/design-and-implementation-of-image-super-resolution-for-myocardial-image" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59494.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">375</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6220</span> A Method of the Semantic on Image Auto-Annotation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lin%20Huo">Lin Huo</a>, <a href="https://publications.waset.org/abstracts/search?q=Xianwei%20Liu"> Xianwei Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Jingxiong%20Zhou"> Jingxiong Zhou</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recently, due to the existence of semantic gap between image visual features and human concepts, the semantic of image auto-annotation has become an important topic. Firstly, by extract low-level visual features of the image, and the corresponding Hash method, mapping the feature into the corresponding Hash coding, eventually, transformed that into a group of binary string and store it, image auto-annotation by search is a popular method, we can use it to design and implement a method of image semantic auto-annotation. Finally, Through the test based on the Corel image set, and the results show that, this method is effective. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20auto-annotation" title="image auto-annotation">image auto-annotation</a>, <a href="https://publications.waset.org/abstracts/search?q=color%20correlograms" title=" color correlograms"> color correlograms</a>, <a href="https://publications.waset.org/abstracts/search?q=Hash%20code" title=" Hash code"> Hash code</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20retrieval" title=" image retrieval"> image retrieval</a> </p> <a href="https://publications.waset.org/abstracts/15628/a-method-of-the-semantic-on-image-auto-annotation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15628.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">497</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6219</span> Analysis of Detection Concealed Objects Based on Multispectral and Hyperspectral Signatures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Kastek">M. Kastek</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Kowalski"> M. Kowalski</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Szustakowski"> M. Szustakowski</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Polakowski"> H. Polakowski</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Sosnowski"> T. Sosnowski</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Development of highly efficient security systems is one of the most urgent topics for science and engineering. There are many kinds of threats and many methods of prevention. It is very important to detect a threat as early as possible in order to neutralize it. One of the very challenging problems is detection of dangerous objects hidden under human鈥檚 clothing. This problem is particularly important for safety of airport passengers. In order to develop methods and algorithms to detect hidden objects it is necessary to determine the thermal signatures of such objects of interest. The laboratory measurements were conducted to determine the thermal signatures of dangerous tools hidden under various clothes in different ambient conditions. Cameras used for measurements were working in spectral range 0.6-12.5 渭m An infrared imaging Fourier transform spectroradiometer was also used, working in spectral range 7.7-11.7 渭m. Analysis of registered thermograms and hyperspectral datacubes has yielded the thermal signatures for two types of guns, two types of knives and home-made explosive bombs. The determined thermal signatures will be used in the development of method and algorithms of image analysis implemented in proposed monitoring systems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hyperspectral%20detection" title="hyperspectral detection">hyperspectral detection</a>, <a href="https://publications.waset.org/abstracts/search?q=nultispectral%20detection" title=" nultispectral detection"> nultispectral detection</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=monitoring%20systems" title=" monitoring systems"> monitoring systems</a> </p> <a href="https://publications.waset.org/abstracts/7795/analysis-of-detection-concealed-objects-based-on-multispectral-and-hyperspectral-signatures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7795.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">348</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6218</span> Deployment of Matrix Transpose in Digital Image Encryption</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Okike%20Benjamin">Okike Benjamin</a>, <a href="https://publications.waset.org/abstracts/search?q=Garba%20E%20J.%20D."> Garba E J. D.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Encryption is used to conceal information from prying eyes. Presently, information and data encryption are common due to the volume of data and information in transit across the globe on daily basis. Image encryption is yet to receive the attention of the researchers as deserved. In other words, video and multimedia documents are exposed to unauthorized accessors. The authors propose image encryption using matrix transpose. An algorithm that would allow image encryption is developed. In this proposed image encryption technique, the image to be encrypted is split into parts based on the image size. Each part is encrypted separately using matrix transpose. The actual encryption is on the picture elements (pixel) that make up the image. After encrypting each part of the image, the positions of the encrypted images are swapped before transmission of the image can take place. Swapping the positions of the images is carried out to make the encrypted image more robust for any cryptanalyst to decrypt. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20encryption" title="image encryption">image encryption</a>, <a href="https://publications.waset.org/abstracts/search?q=matrices" title=" matrices"> matrices</a>, <a href="https://publications.waset.org/abstracts/search?q=pixel" title=" pixel"> pixel</a>, <a href="https://publications.waset.org/abstracts/search?q=matrix%20transpose" title=" matrix transpose "> matrix transpose </a> </p> <a href="https://publications.waset.org/abstracts/48717/deployment-of-matrix-transpose-in-digital-image-encryption" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48717.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">421</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6217</span> Voxel Models as Input for Heat Transfer Simulations with Siemens NX Based on X-Ray Microtomography Images of Random Fibre Reinforced Composites</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Steven%20Latr%C3%A9">Steven Latr茅</a>, <a href="https://publications.waset.org/abstracts/search?q=Frederik%20Desplentere"> Frederik Desplentere</a>, <a href="https://publications.waset.org/abstracts/search?q=Ilya%20Straumit"> Ilya Straumit</a>, <a href="https://publications.waset.org/abstracts/search?q=Stepan%20V.%20Lomov"> Stepan V. Lomov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A method is proposed in order to create a three-dimensional finite element model representing fibre reinforced insulation materials for the simulation software Siemens NX. VoxTex software, a tool for quantification of 碌CT images of fibrous materials, is used for the transformation of microtomography images of random fibre reinforced composites into finite element models. An automatic tool was developed to execute the import of the models to the thermal solver module of Siemens NX. The paper describes the numerical tools used for the image quantification and the transformation and illustrates them on several thermal simulations of fibre reinforced insulation blankets filled with low thermal conductive fillers. The calculation of thermal conductivity is validated by comparison with the experimental data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=analysis" title="analysis">analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=modelling" title=" modelling"> modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal" title=" thermal"> thermal</a>, <a href="https://publications.waset.org/abstracts/search?q=voxel" title=" voxel"> voxel</a> </p> <a href="https://publications.waset.org/abstracts/70059/voxel-models-as-input-for-heat-transfer-simulations-with-siemens-nx-based-on-x-ray-microtomography-images-of-random-fibre-reinforced-composites" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70059.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">287</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6216</span> Fruit Identification System in Sweet Orange Citrus (L.) Osbeck Using Thermal Imaging and Fuzzy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ingrid%20Argote">Ingrid Argote</a>, <a href="https://publications.waset.org/abstracts/search?q=John%20Archila"> John Archila</a>, <a href="https://publications.waset.org/abstracts/search?q=Marcelo%20Becker"> Marcelo Becker</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In agriculture, intelligent systems applications have generated great advances in automating some of the processes in the production chain. In order to improve the efficiency of those systems is proposed a vision system to estimate the amount of fruits in sweet orange trees. This work presents a system proposal using capture of thermal images and fuzzy logic. A bibliographical review has been done to analyze the state-of-the-art of the different systems used in fruit recognition, and also the different applications of thermography in agricultural systems. The algorithm developed for this project uses the metrics of the fuzzines parameter to the contrast improvement and segmentation of the image, for the counting algorith m was used the Hough transform. In order to validate the proposed algorithm was created a bank of images of sweet orange Citrus (L.) Osbeck acquired in the Maring谩 Farm. The tests with the algorithm Indicated that the variation of the tree branch temperature and the fruit is not very high, Which makes the process of image segmentation using this differentiates, This Increases the amount of false positives in the fruit counting algorithm. Recognition of fruits isolated with the proposed algorithm present an overall accuracy of 90.5 % and grouped fruits. The accuracy was 81.3 %. The experiments show the need for a more suitable hardware to have a better recognition of small temperature changes in the image. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Agricultural%20systems" title="Agricultural systems">Agricultural systems</a>, <a href="https://publications.waset.org/abstracts/search?q=Citrus" title="Citrus">Citrus</a>, <a href="https://publications.waset.org/abstracts/search?q=Fuzzy%20logic" title="Fuzzy logic">Fuzzy logic</a>, <a href="https://publications.waset.org/abstracts/search?q=Thermal%20images." title=" Thermal images. "> Thermal images. </a> </p> <a href="https://publications.waset.org/abstracts/39767/fruit-identification-system-in-sweet-orange-citrus-l-osbeck-using-thermal-imaging-and-fuzzy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39767.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">229</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6215</span> Two Major Methods to Control Thermal Resistance of Focus Ring for Process Uniformity Enhance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jin-Uk%20Park">Jin-Uk Park</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recently, the semiconductor industry is rapidly demanding complicated structures and mass production. From the point of view of mass production, the ETCH industry is concentrating on maintaining the ER (Etch rate) of the wafer edge constant regardless of changes over time. In this study, two major thermal factors affecting process were identified and controlled. First, the filler of the thermal pad was studied. Second, the significant difference of handling the thermal pad during PM was studied. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=etcher" title="etcher">etcher</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20pad" title=" thermal pad"> thermal pad</a>, <a href="https://publications.waset.org/abstracts/search?q=wet%20cleaning" title=" wet cleaning"> wet cleaning</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20conductivity" title=" thermal conductivity"> thermal conductivity</a> </p> <a href="https://publications.waset.org/abstracts/143443/two-major-methods-to-control-thermal-resistance-of-focus-ring-for-process-uniformity-enhance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/143443.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">193</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6214</span> Using the Transient Plane Source Method for Measuring Thermal Parameters of Electroceramics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Peter%20Krupa">Peter Krupa</a>, <a href="https://publications.waset.org/abstracts/search?q=Svetoz%C3%A1r%20Malinari%C4%8D"> Svetoz谩r Malinari膷</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Transient plane source method has been used to measure the thermal diffusivity and thermal conductivity of a compact isostatic electro-ceramics at room temperature. The samples were fired at temperatures from 100 up to 1320 degrees Celsius in steps of 50. Bulk density and specific heat capacity were also measured with their corresponding standard uncertainties. The results were compared with further thermal analysis (dilatometry and thermogravimetry). Structural processes during firing were discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=TPS%20method" title="TPS method">TPS method</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20conductivity" title=" thermal conductivity"> thermal conductivity</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20diffusivity" title=" thermal diffusivity"> thermal diffusivity</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20analysis" title=" thermal analysis"> thermal analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=electro-ceramics" title=" electro-ceramics"> electro-ceramics</a>, <a href="https://publications.waset.org/abstracts/search?q=firing" title=" firing"> firing</a> </p> <a href="https://publications.waset.org/abstracts/8438/using-the-transient-plane-source-method-for-measuring-thermal-parameters-of-electroceramics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8438.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">489</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6213</span> Performance of Hybrid Image Fusion: Implementation of Dual-Tree Complex Wavelet Transform Technique </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Manoj%20Gupta">Manoj Gupta</a>, <a href="https://publications.waset.org/abstracts/search?q=Nirmendra%20Singh%20Bhadauria"> Nirmendra Singh Bhadauria</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Most of the applications in image processing require high spatial and high spectral resolution in a single image. For example satellite image system, the traffic monitoring system, and long range sensor fusion system all use image processing. However, most of the available equipment is not capable of providing this type of data. The sensor in the surveillance system can only cover the view of a small area for a particular focus, yet the demanding application of this system requires a view with a high coverage of the field. Image fusion provides the possibility of combining different sources of information. In this paper, we have decomposed the image using DTCWT and then fused using average and hybrid of (maxima and average) pixel level techniques and then compared quality of both the images using PSNR. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20fusion" title="image fusion">image fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=DWT" title=" DWT"> DWT</a>, <a href="https://publications.waset.org/abstracts/search?q=DT-CWT" title=" DT-CWT"> DT-CWT</a>, <a href="https://publications.waset.org/abstracts/search?q=PSNR" title=" PSNR"> PSNR</a>, <a href="https://publications.waset.org/abstracts/search?q=average%20image%20fusion" title=" average image fusion"> average image fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20image%20fusion" title=" hybrid image fusion"> hybrid image fusion</a> </p> <a href="https://publications.waset.org/abstracts/19207/performance-of-hybrid-image-fusion-implementation-of-dual-tree-complex-wavelet-transform-technique" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19207.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">606</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6212</span> Assessment of Image Databases Used for Human Skin Detection Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saleh%20Alshehri">Saleh Alshehri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Human skin detection is a vital step in many applications. Some of the applications are critical especially those related to security. This leverages the importance of a high-performance detection algorithm. To validate the accuracy of the algorithm, image databases are usually used. However, the suitability of these image databases is still questionable. It is suggested that the suitability can be measured mainly by the span the database covers of the color space. This research investigates the validity of three famous image databases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=image%20databases" title="image databases">image databases</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=pattern%20recognition" title=" pattern recognition"> pattern recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20networks" title=" neural networks"> neural networks</a> </p> <a href="https://publications.waset.org/abstracts/87836/assessment-of-image-databases-used-for-human-skin-detection-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/87836.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">271</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6211</span> A Novel Combination Method for Computing the Importance Map of Image</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20Absetan">Ahmad Absetan</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahdi%20Nooshyar"> Mahdi Nooshyar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The importance map is an image-based measure and is a core part of the resizing algorithm. Importance measures include image gradients, saliency and entropy, as well as high level cues such as face detectors, motion detectors and more. In this work we proposed a new method to calculate the importance map, the importance map is generated automatically using a novel combination of image edge density and Harel saliency measurement. Experiments of different type images demonstrate that our method effectively detects prominent areas can be used in image resizing applications to aware important areas while preserving image quality. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=content-aware%20image%20resizing" title="content-aware image resizing">content-aware image resizing</a>, <a href="https://publications.waset.org/abstracts/search?q=visual%20saliency" title=" visual saliency"> visual saliency</a>, <a href="https://publications.waset.org/abstracts/search?q=edge%20density" title=" edge density"> edge density</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20warping" title=" image warping"> image warping</a> </p> <a href="https://publications.waset.org/abstracts/35692/a-novel-combination-method-for-computing-the-importance-map-of-image" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35692.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">582</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6210</span> Blind Data Hiding Technique Using Interpolation of Subsampled Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Singara%20Singh%20Kasana">Singara Singh Kasana</a>, <a href="https://publications.waset.org/abstracts/search?q=Pankaj%20Garg"> Pankaj Garg</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a blind data hiding technique based on interpolation of sub sampled versions of a cover image is proposed. Sub sampled image is taken as a reference image and an interpolated image is generated from this reference image. Then difference between original cover image and interpolated image is used to embed secret data. Comparisons with the existing interpolation based techniques show that proposed technique provides higher embedding capacity and better visual quality marked images. Moreover, the performance of the proposed technique is more stable for different images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=interpolation" title="interpolation">interpolation</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20subsampling" title=" image subsampling"> image subsampling</a>, <a href="https://publications.waset.org/abstracts/search?q=PSNR" title=" PSNR"> PSNR</a>, <a href="https://publications.waset.org/abstracts/search?q=SIM" title=" SIM"> SIM</a> </p> <a href="https://publications.waset.org/abstracts/18926/blind-data-hiding-technique-using-interpolation-of-subsampled-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18926.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">578</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6209</span> Self-Image of Police Officers</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Leo%20Carlo%20B.%20Rondina">Leo Carlo B. Rondina</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Self-image is an important factor to improve the self-esteem of the personnel. The purpose of the study is to determine the self-image of the police. The respondents were the 503 policemen assigned in different Police Station in Davao City, and they were chosen with the used of random sampling. With the used of Exploratory Factor Analysis (EFA), latent construct variables of police image were identified as follows; professionalism, obedience, morality and justice and fairness. Further, ordinal regression indicates statistical characteristics on ages 21-40 which means the age of the respondent statistically improves self-image. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=police%20image" title="police image">police image</a>, <a href="https://publications.waset.org/abstracts/search?q=exploratory%20factor%20analysis" title=" exploratory factor analysis"> exploratory factor analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=ordinal%20regression" title=" ordinal regression"> ordinal regression</a>, <a href="https://publications.waset.org/abstracts/search?q=Galatea%20effect" title=" Galatea effect"> Galatea effect</a> </p> <a href="https://publications.waset.org/abstracts/75550/self-image-of-police-officers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75550.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">287</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6208</span> Evaluating Classification with Efficacy Metrics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Guofan%20Shao">Guofan Shao</a>, <a href="https://publications.waset.org/abstracts/search?q=Lina%20Tang"> Lina Tang</a>, <a href="https://publications.waset.org/abstracts/search?q=Hao%20Zhang"> Hao Zhang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The values of image classification accuracy are affected by class size distributions and classification schemes, making it difficult to compare the performance of classification algorithms across different remote sensing data sources and classification systems. Based on the term efficacy from medicine and pharmacology, we have developed the metrics of image classification efficacy at the map and class levels. The novelty of this approach is that a baseline classification is involved in computing image classification efficacies so that the effects of class statistics are reduced. Furthermore, the image classification efficacies are interpretable and comparable, and thus, strengthen the assessment of image data classification methods. We use real-world and hypothetical examples to explain the use of image classification efficacies. The metrics of image classification efficacy meet the critical need to rectify the strategy for the assessment of image classification performance as image classification methods are becoming more diversified. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=accuracy%20assessment" title="accuracy assessment">accuracy assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=efficacy" title=" efficacy"> efficacy</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20classification" title=" image classification"> image classification</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=uncertainty" title=" uncertainty"> uncertainty</a> </p> <a href="https://publications.waset.org/abstracts/142555/evaluating-classification-with-efficacy-metrics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/142555.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">210</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6207</span> Marker-Controlled Level-Set for Segmenting Breast Tumor from Thermal Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Swathi%20Gopakumar">Swathi Gopakumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Sruthi%20Krishna"> Sruthi Krishna</a>, <a href="https://publications.waset.org/abstracts/search?q=Shivasubramani%20Krishnamoorthy"> Shivasubramani Krishnamoorthy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Contactless, painless and radiation-free thermal imaging technology is one of the preferred screening modalities for detection of breast cancer. However, poor signal to noise ratio and the inexorable need to preserve edges defining cancer cells and normal cells, make the segmentation process difficult and hence unsuitable for computer-aided diagnosis of breast cancer. This paper presents key findings from a research conducted on the appraisal of two promising techniques, for the detection of breast cancer: (I) marker-controlled, Level-set segmentation of anisotropic diffusion filtered preprocessed image versus (II) Segmentation using marker-controlled level-set on a Gaussian-filtered image. Gaussian-filtering processes the image uniformly, whereas anisotropic filtering processes only in specific areas of a thermographic image. The pre-processed (Gaussian-filtered and anisotropic-filtered) images of breast samples were then applied for segmentation. The segmentation of breast starts with initial level-set function. In this study, marker refers to the position of the image to which initial level-set function is applied. The markers are generally placed on the left and right side of the breast, which may vary with the breast size. The proposed method was carried out on images from an online database with samples collected from women of varying breast characteristics. It was observed that the breast was able to be segmented out from the background by adjustment of the markers. From the results, it was observed that as a pre-processing technique, anisotropic filtering with level-set segmentation, preserved the edges more effectively than Gaussian filtering. Segmented image, by application of anisotropic filtering was found to be more suitable for feature extraction, enabling automated computer-aided diagnosis of breast cancer. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=anisotropic%20diffusion" title="anisotropic diffusion">anisotropic diffusion</a>, <a href="https://publications.waset.org/abstracts/search?q=breast" title=" breast"> breast</a>, <a href="https://publications.waset.org/abstracts/search?q=Gaussian" title=" Gaussian"> Gaussian</a>, <a href="https://publications.waset.org/abstracts/search?q=level-set" title=" level-set"> level-set</a>, <a href="https://publications.waset.org/abstracts/search?q=thermograms" title=" thermograms"> thermograms</a> </p> <a href="https://publications.waset.org/abstracts/85030/marker-controlled-level-set-for-segmenting-breast-tumor-from-thermal-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/85030.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">380</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6206</span> Texture Analysis of Grayscale Co-Occurrence Matrix on Mammographic Indexed Image</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Sushma">S. Sushma</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Balasubramanian"> S. Balasubramanian</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20C.%20Latha"> K. C. Latha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The mammographic image of breast cancer compressed and synthesized to get co-efficient values which will be converted (5x5) matrix to get ROI image where we get the highest value of effected region and with the same ideology the technique has been extended to differentiate between Calcification and normal cell image using mean value derived from 5x5 matrix values <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=texture%20analysis" title="texture analysis">texture analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=mammographic%20image" title=" mammographic image"> mammographic image</a>, <a href="https://publications.waset.org/abstracts/search?q=partitioned%20gray%20scale%20co-oocurance%20matrix" title=" partitioned gray scale co-oocurance matrix"> partitioned gray scale co-oocurance matrix</a>, <a href="https://publications.waset.org/abstracts/search?q=co-efficient" title=" co-efficient "> co-efficient </a> </p> <a href="https://publications.waset.org/abstracts/17516/texture-analysis-of-grayscale-co-occurrence-matrix-on-mammographic-indexed-image" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17516.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">533</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6205</span> Study on the Thermal Mixing of Steam and Coolant in the Hybrid Safety Injection Tank</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sung%20Uk%20Ryu">Sung Uk Ryu</a>, <a href="https://publications.waset.org/abstracts/search?q=Byoung%20Gook%20Jeon"> Byoung Gook Jeon</a>, <a href="https://publications.waset.org/abstracts/search?q=Sung-Jae%20Yi"> Sung-Jae Yi</a>, <a href="https://publications.waset.org/abstracts/search?q=Dong-Jin%20Euh"> Dong-Jin Euh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In such passive safety injection systems in the nuclear power plant as Core Makeup Tank (CMT) and Hybrid Safety Injection Tank, various thermal-hydraulic phenomena including the direct contact condensation of steam and the thermal stratification of coolant occur. These phenomena are also closely related to the performance of the system. Depending on the condensation rate of the steam injected to the tank, the injection of the coolant and pressure equalizing timings of the tank are decided. The steam injected to the tank from the upper nozzle penetrates the coolant and induces a direct contact condensation. In the present study, the direct contact condensation of steam and the thermal mixing between the steam and coolant were examined by using the Particle Image Velocimetry (PIV) technique. Especially, by altering the size of the nozzle from which the steam is injected, the influence of steam injection velocity on the thermal mixing with coolant and condensation shall be comprehended, while also investigating the influence of condensation on the pressure variation inside the tank. Even though the amounts of steam inserted were the same in three different nozzle size conditions, it was found that the velocity of pressure rise becomes lower as the steam injection area decreases. Also, as the steam injection area increases, the thickness of the zone within which the coolant鈥檚 temperature decreases. Thereby, the amount of steam condensed by the direct contact condensation also decreases. The results derived from the present study can be utilized for the detailed design of a passive safety injection system, as well as for modeling the direct contact condensation triggered by the steam jet鈥檚 penetration into the coolant. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=passive%20safety%20injection%20systems" title="passive safety injection systems">passive safety injection systems</a>, <a href="https://publications.waset.org/abstracts/search?q=steam%20penetration" title=" steam penetration"> steam penetration</a>, <a href="https://publications.waset.org/abstracts/search?q=direct%20contact%20condensation" title=" direct contact condensation"> direct contact condensation</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20image%20velocimetry" title=" particle image velocimetry"> particle image velocimetry</a> </p> <a href="https://publications.waset.org/abstracts/62498/study-on-the-thermal-mixing-of-steam-and-coolant-in-the-hybrid-safety-injection-tank" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62498.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">395</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6204</span> Thermal Properties of the Ground in Cyprus and Their Correlations and Effect on the Efficiency of Ground Heat Exchangers</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=G.%20A.%20Florides">G. A. Florides</a>, <a href="https://publications.waset.org/abstracts/search?q=E.%20Theofanous"> E. Theofanous</a>, <a href="https://publications.waset.org/abstracts/search?q=I.%20Iosif-Stylianou"> I. Iosif-Stylianou</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Christodoulides"> P. Christodoulides</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Kalogirou"> S. Kalogirou</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20Messarites"> V. Messarites</a>, <a href="https://publications.waset.org/abstracts/search?q=Z.%20Zomeni"> Z. Zomeni</a>, <a href="https://publications.waset.org/abstracts/search?q=E.%20Tsiolakis"> E. Tsiolakis</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20D.%20Pouloupatis"> P. D. Pouloupatis</a>, <a href="https://publications.waset.org/abstracts/search?q=G.%20P.%20Panayiotou"> G. P. Panayiotou</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ground Coupled Heat Pumps (GCHPs) exploit effectively the heat capacity of the ground, with the use of Ground Heat Exchangers (GHE). Depending on the mode of operation of the GCHPs, GHEs dissipate or absorb heat from the ground. For sizing the GHE the thermal properties of the ground need to be known. This paper gives information about the density, thermal conductivity, specific heat and thermal diffusivity of various lithologies encountered in Cyprus with various relations between these properties being examined through comparison and modeling. The results show that the most important correlation is the one encountered between thermal conductivity and thermal diffusivity with both properties showing similar response to the inlet and outlet flow temperature of vertical and horizontal heat exchangers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ground%20heat%20exchangers" title="ground heat exchangers">ground heat exchangers</a>, <a href="https://publications.waset.org/abstracts/search?q=ground%20thermal%20conductivity" title=" ground thermal conductivity"> ground thermal conductivity</a>, <a href="https://publications.waset.org/abstracts/search?q=ground%20thermal%20diffusivity" title=" ground thermal diffusivity"> ground thermal diffusivity</a>, <a href="https://publications.waset.org/abstracts/search?q=ground%20thermal%20properties" title=" ground thermal properties"> ground thermal properties</a> </p> <a href="https://publications.waset.org/abstracts/2459/thermal-properties-of-the-ground-in-cyprus-and-their-correlations-and-effect-on-the-efficiency-of-ground-heat-exchangers" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2459.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">380</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=thermal%20image&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=thermal%20image&page=3">3</a></li> <li class="page-item"><a class="page-link" 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