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released 2020-02-24</a> </span> </div> </div> <div class="content"> <form method="GET" action="/search/cs" aria-role="search"> Searching in archive <strong>cs</strong>. <a href="/search/?searchtype=author&query=Mehmood%2C+I">Search in all archives.</a> <div class="field has-addons-tablet"> <div class="control is-expanded"> <label for="query" class="hidden-label">Search term or terms</label> <input class="input is-medium" id="query" name="query" placeholder="Search term..." type="text" value="Mehmood, I"> </div> <div class="select control is-medium"> <label class="is-hidden" for="searchtype">Field</label> <select class="is-medium" id="searchtype" name="searchtype"><option value="all">All fields</option><option value="title">Title</option><option selected value="author">Author(s)</option><option value="abstract">Abstract</option><option value="comments">Comments</option><option value="journal_ref">Journal reference</option><option value="acm_class">ACM classification</option><option 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Search</a> </div> </div> <input type="hidden" name="order" value="-announced_date_first"> <input type="hidden" name="size" value="50"> </form> <div class="level breathe-horizontal"> <div class="level-left"> <form method="GET" action="/search/"> <div style="display: none;"> <select id="searchtype" name="searchtype"><option value="all">All fields</option><option value="title">Title</option><option selected value="author">Author(s)</option><option value="abstract">Abstract</option><option value="comments">Comments</option><option value="journal_ref">Journal reference</option><option value="acm_class">ACM classification</option><option value="msc_class">MSC classification</option><option value="report_num">Report number</option><option value="paper_id">arXiv identifier</option><option value="doi">DOI</option><option value="orcid">ORCID</option><option value="license">License (URI)</option><option value="author_id">arXiv author ID</option><option value="help">Help pages</option><option value="full_text">Full text</option></select> <input id="query" name="query" type="text" value="Mehmood, I"> <ul id="abstracts"><li><input checked id="abstracts-0" name="abstracts" type="radio" value="show"> <label for="abstracts-0">Show abstracts</label></li><li><input id="abstracts-1" name="abstracts" type="radio" value="hide"> <label for="abstracts-1">Hide abstracts</label></li></ul> </div> <div class="box field is-grouped is-grouped-multiline level-item"> <div class="control"> <span class="select is-small"> <select id="size" name="size"><option value="25">25</option><option selected value="50">50</option><option value="100">100</option><option value="200">200</option></select> </span> <label for="size">results per page</label>. </div> <div class="control"> <label for="order">Sort results by</label> <span class="select is-small"> <select id="order" name="order"><option selected value="-announced_date_first">Announcement date (newest first)</option><option 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class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/ACCESS.2023.3320809">10.1109/ACCESS.2023.3320809 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Perceptual Tone Mapping Model for High Dynamic Range Imaging </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Mehmood%2C+I">Imran Mehmood</a>, <a href="/search/cs?searchtype=author&query=Shi%2C+X">Xinye Shi</a>, <a href="/search/cs?searchtype=author&query=Khan%2C+M+U">M. Usman Khan</a>, <a href="/search/cs?searchtype=author&query=Luo%2C+M+R">Ming Ronnier Luo</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2309.16975v1-abstract-short" style="display: inline;"> One of the key challenges in tone mapping is to preserve the perceptual quality of high dynamic range (HDR) images when mapping them to standard dynamic range (SDR) displays. Traditional tone mapping operators (TMOs) compress the luminance of HDR images without considering the surround and display conditions emanating into suboptimal results. Current research addresses this challenge by incorporat… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2309.16975v1-abstract-full').style.display = 'inline'; document.getElementById('2309.16975v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2309.16975v1-abstract-full" style="display: none;"> One of the key challenges in tone mapping is to preserve the perceptual quality of high dynamic range (HDR) images when mapping them to standard dynamic range (SDR) displays. Traditional tone mapping operators (TMOs) compress the luminance of HDR images without considering the surround and display conditions emanating into suboptimal results. Current research addresses this challenge by incorporating perceptual color appearance attributes. In this work, we propose a TMO (TMOz) that leverages CIECAM16 perceptual attributes, i.e., brightness, colorfulness, and hue. TMOz accounts for the effects of both the surround and the display conditions to achieve more optimal colorfulness reproduction. The perceptual brightness is compressed, and the perceptual color scales, i.e., colorfulness and hue are derived from HDR images by employing CIECAM16 color adaptation equations. A psychophysical experiment was conducted to automate the brightness compression parameter. The model employs fully automatic and adaptive approach, obviating the requirement for manual parameter selection. TMOz was evaluated in terms of contrast, colorfulness and overall image quality. The objective and subjective evaluation methods revealed that the proposed model outperformed the state-of-the-art TMOs. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2309.16975v1-abstract-full').style.display = 'none'; document.getElementById('2309.16975v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 29 September, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1510.02177">arXiv:1510.02177</a> <span> [<a href="https://arxiv.org/pdf/1510.02177">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Multimedia">cs.MM</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Information Retrieval">cs.IR</span> </div> </div> <p class="title is-5 mathjax"> Ontology-based Secure Retrieval of Semantically Significant Visual Contents </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Muhammad%2C+K">Khan Muhammad</a>, <a href="/search/cs?searchtype=author&query=Mehmood%2C+I">Irfan Mehmood</a>, <a href="/search/cs?searchtype=author&query=Lee%2C+M+Y">Mi Young Lee</a>, <a href="/search/cs?searchtype=author&query=Ji%2C+S+M">Su Mi Ji</a>, <a href="/search/cs?searchtype=author&query=Baik%2C+S+W">Sung Wook Baik</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1510.02177v1-abstract-short" style="display: inline;"> Image classification is an enthusiastic research field where large amount of image data is classified into various classes based on their visual contents. Researchers have presented various low-level features-based techniques for classifying images into different categories. However, efficient and effective classification and retrieval is still a challenging problem due to complex nature of visual… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1510.02177v1-abstract-full').style.display = 'inline'; document.getElementById('1510.02177v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1510.02177v1-abstract-full" style="display: none;"> Image classification is an enthusiastic research field where large amount of image data is classified into various classes based on their visual contents. Researchers have presented various low-level features-based techniques for classifying images into different categories. However, efficient and effective classification and retrieval is still a challenging problem due to complex nature of visual contents. In addition, the traditional information retrieval techniques are vulnerable to security risks, making it easy for attackers to retrieve personal visual contents such as patients records and law enforcement agencies databases. Therefore, we propose a novel ontology-based framework using image steganography for secure image classification and information retrieval. The proposed framework uses domain-specific ontology for mapping the low-level image features to high-level concepts of ontologies which consequently results in efficient classification. Furthermore, the proposed method utilizes image steganography for hiding the image semantics as a secret message inside them, making the information retrieval process secure from third parties. The proposed framework minimizes the computational complexity of traditional techniques, increasing its suitability for secure and real-time visual contents retrieval from personalized image databases. Experimental results confirm the efficiency, effectiveness, and security of the proposed framework as compared with other state-of-the-art systems. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1510.02177v1-abstract-full').style.display = 'none'; document.getElementById('1510.02177v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 October, 2015; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2015. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">A short paper of 11 pages for secure visual contents retrieval.The original version can be accessed at this link: http://www.kingpc.or.kr/inc_html/index.html</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Khan Muhammad, Irfan Mehmood, Mi Young Lee, Su Mi Ji, Sung Wook Baik, "Ontology-based Secure Retrieval of Semantically Significant Visual Contents," JOURNAL OF KOREAN INSTITUTE OF NEXT GENERATION COMPUTING, vol. 11, pp. 87-96, 2015 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1506.02100">arXiv:1506.02100</a> <span> [<a href="https://arxiv.org/pdf/1506.02100">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Multimedia">cs.MM</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1007/s11042-015-2671-9">10.1007/s11042-015-2671-9 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> A novel magic LSB substitution method (M-LSB-SM) using multi-level encryption and achromatic component of an image </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Muhammad%2C+K">Khan Muhammad</a>, <a href="/search/cs?searchtype=author&query=Sajjad%2C+M">Muhammad Sajjad</a>, <a href="/search/cs?searchtype=author&query=Mehmood%2C+I">Irfan Mehmood</a>, <a href="/search/cs?searchtype=author&query=Rho%2C+S">Seungmin Rho</a>, <a href="/search/cs?searchtype=author&query=Baik%2C+S+W">Sung Wook Baik</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1506.02100v1-abstract-short" style="display: inline;"> Image Steganography is a thriving research area of information security where secret data is embedded in images to hide its existence while getting the minimum possible statistical detectability. This paper proposes a novel magic least significant bit substitution method (M-LSB-SM) for RGB images. The proposed method is based on the achromatic component (I-plane) of the hue-saturation-intensity (H… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1506.02100v1-abstract-full').style.display = 'inline'; document.getElementById('1506.02100v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1506.02100v1-abstract-full" style="display: none;"> Image Steganography is a thriving research area of information security where secret data is embedded in images to hide its existence while getting the minimum possible statistical detectability. This paper proposes a novel magic least significant bit substitution method (M-LSB-SM) for RGB images. The proposed method is based on the achromatic component (I-plane) of the hue-saturation-intensity (HSI) color model and multi-level encryption (MLE) in the spatial domain. The input image is transposed and converted into an HSI color space. The I-plane is divided into four sub-images of equal size, rotating each sub-image with a different angle using a secret key. The secret information is divided into four blocks, which are then encrypted using an MLE algorithm (MLEA). Each sub-block of the message is embedded into one of the rotated sub-images based on a specific pattern using magic LSB substitution. Experimental results validate that the proposed method not only enhances the visual quality of stego images but also provides good imperceptibility and multiple security levels as compared to several existing prominent methods. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1506.02100v1-abstract-full').style.display = 'none'; document.getElementById('1506.02100v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 5 June, 2015; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2015. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">This paper has been published in Multimedia Tools and Applications Journal with impact factor=1.058. The readers can study the formatted paper using the following link: http://link.springer.com/article/10.1007/s11042-015-2671-9. Please use sci-hub.org for downloading this paper if you are unable to access it freely or email us at khan.muhammad.icp@gmail.com</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Multimedia Tools and Applications, pp. 1-27, 2015 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1502.07041">arXiv:1502.07041</a> <span> [<a href="https://arxiv.org/pdf/1502.07041">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Retrieval">cs.IR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> Describing Colors, Textures and Shapes for Content Based Image Retrieval - A Survey </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Ahmad%2C+J">Jamil Ahmad</a>, <a href="/search/cs?searchtype=author&query=Sajjad%2C+M">Muhammad Sajjad</a>, <a href="/search/cs?searchtype=author&query=Mehmood%2C+I">Irfan Mehmood</a>, <a href="/search/cs?searchtype=author&query=Rho%2C+S">Seungmin Rho</a>, <a href="/search/cs?searchtype=author&query=Baik%2C+S+W">Sung Wook Baik</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1502.07041v1-abstract-short" style="display: inline;"> Visual media has always been the most enjoyed way of communication. From the advent of television to the modern day hand held computers, we have witnessed the exponential growth of images around us. Undoubtedly it's a fact that they carry a lot of information in them which needs be utilized in an effective manner. Hence intense need has been felt to efficiently index and store large image collecti… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1502.07041v1-abstract-full').style.display = 'inline'; document.getElementById('1502.07041v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1502.07041v1-abstract-full" style="display: none;"> Visual media has always been the most enjoyed way of communication. From the advent of television to the modern day hand held computers, we have witnessed the exponential growth of images around us. Undoubtedly it's a fact that they carry a lot of information in them which needs be utilized in an effective manner. Hence intense need has been felt to efficiently index and store large image collections for effective and on- demand retrieval. For this purpose low-level features extracted from the image contents like color, texture and shape has been used. Content based image retrieval systems employing these features has proven very successful. Image retrieval has promising applications in numerous fields and hence has motivated researchers all over the world. New and improved ways to represent visual content are being developed each day. Tremendous amount of research has been carried out in the last decade. In this paper we will present a detailed overview of some of the powerful color, texture and shape descriptors for content based image retrieval. A comparative analysis will also be carried out for providing an insight into outstanding challenges in this field. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1502.07041v1-abstract-full').style.display = 'none'; document.getElementById('1502.07041v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 24 February, 2015; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2015. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> (2014), Journal of Platform Technology 2(4): 34-48 </p> </li> </ol> <div class="is-hidden-tablet"> <!-- feedback for mobile only --> <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 2020-02-24</a> </span> </div> </div> </main> 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