Analysis of Histogram Asymmetry for Waste Recognition

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for Waste Recognition</title> <meta name="description" content="Analysis of Histogram Asymmetry for Waste Recognition"> <meta name="keywords" content="Computer vision, environmental protection, image processing, waste management."> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <meta name="citation_title" content="Analysis of Histogram Asymmetry for Waste Recognition"> <meta name="citation_author" content="Janusz Bobulski"> <meta name="citation_author" content="Kamila Pasternak"> <meta name="citation_publication_date" content="2023/10/16"> <meta name="citation_journal_title" content="International Journal of Computer and Information Engineering"> <meta name="citation_volume" content="17"> <meta name="citation_issue" content="10"> <meta name="citation_firstpage" content="583"> <meta name="citation_lastpage" content="586"> <meta name="citation_pdf_url" 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class="card-text"><strong>Abstract:</strong></p> <p>Despite many years of effort and research, the problem of waste management is still current. There is a lack of fast and effective algorithms for classifying individual waste fractions. Many programs and projects improve statistics on the percentage of waste recycled every year. In these efforts, it is worth using modern Computer Vision techniques supported by artificial intelligence. In the article, we present a method of identifying plastic waste based on the asymmetry analysis of the histogram of the image containing the waste. The method is simple but effective (94%), which allows it to be implemented on devices with low computing power, in particular on microcomputers. Such de-vices will be used both at home and in waste sorting plants.</p> <iframe src="https://publications.waset.org/10013309.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Computer%20vision" title="Computer vision">Computer vision</a>, <a href="https://publications.waset.org/search?q=environmental%20protection" title=" environmental protection"> environmental protection</a>, <a href="https://publications.waset.org/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/search?q=waste%20management." title=" waste management."> waste management.</a> </p> <a href="https://publications.waset.org/10013309/analysis-of-histogram-asymmetry-for-waste-recognition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10013309/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10013309/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10013309/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10013309/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10013309/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10013309/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10013309/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10013309/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10013309/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10013309/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10013309.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">312</span> </span> <p class="card-text"><strong>References:</strong></p> <br>[1] Lui, C.; Sharan, L.; Adelson, E.H. Rosenholtz, R. Exploring Features in a Bayesian framework for material recognition. In Proceedings of the 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA; 239–246. <br>[2] Rutqvist, D.; Kleyko, D.; Blomstedt, F. An automated machine learning approach for smart waste management systems. IEEE Trans. Ind. Inform2020, 16, 384–392. <br>[3] Zheng, J.; Xu, M.; Cai, M.; Wang, Z.; Yang, M. Modeling group behaviour to study innovation diffusion based on cognition and network: An analysis for the garbage classification system in Shanghai, China. Int. J. Environ. Res. Public Health, 2019, 16, 3349. <br>[4] Costa, B.S.; Bernardes, A.C.; Pereira, J.V.; Zampa, V.H.; Pereira, V.A.; Matos, G.F.; Soares, E.A.; Soares, C.L.; Silva, A.F. Artificial intelligence in automated sorting in trash recycling. In Proceedings of the Anais do XV Encontro Nacional de Inteligência Artificial e Computacional, São Paulo, Brazil, 22–25 October 2018; 198–205. <br>[5] Xu, X.; Qi, X.; Diao, X. Reach on Waste Classification and Identification by Transfer Learning and Lightweight Neural Network. Preprints 2020, 2, 327. <br>[6] Yang, M.; Thung, G. Classification of Trash for Recyclability Status. CS229 Project Report; Stanford University: Stanford, CA, USA, 2016. <br>[7] Awe, O.; Mengistu, R.; Sreedhar, V. Smart trash net: Waste localization and classification. arXiv 2017, preprint. <br>[8] Kennedy, T. OscarNet: Using Transfer Learning to Classify Disposable Waste; CS230 Report: Deep Learning; Stanford University: Stanford, CA, USA, 2018. <br>[9] Kulkarni, H.N.; Raman, N.K.S. Waste Object Detection and Classification; CS230 Report: Deep Learning; Stanford University: Stanford, CA, USA, 2018. <br>[10] Bircanoglu, C.; Atay, M.; Beser, F.; Genc, O.; Kizrak, M.A. RecycleNet: Intelligent Waste Sorting Using Deep Neural Networks. In Proceedings of the 2018 Innovations in Intelligent Systems and Applications (INISTA), Thessaloniki, Greece, 3–5 July 2018. <br>[11] Adedeji, O.; Wang, Z. Intelligent Waste Classification System Using Deep Learning Convolutional Neural Network. Procedia Manuf. 2019, 35, 607–612. <br>[12] Melinte, D.O.; Travediu, A-M; Dumitriu, D.N. Deep Convolutional Neural Networks Object Detector for Real-Time Waste Identification. Applied Sciences2020, 10(20):7301. <br>[13] Sousa, J.; Rebelo, A.; Cardoso, J.S. Automation of Waste Sorting with Deep Learning. In Proceedings of the 2019 XV Workshop de Visão Computacional (WVC), Sao Paulo, Brazil, 9–11 September 2019; 43–48. <br>[14] Chu, Y.; Huang, C.; Xie, X.; Tan, B.; Kamal, S.; Xiong, X. Multilayer Hybrid Deep-Learning Method for Waste Classification and Recycling. Comput. Intell. Neurosci.2018, 2018. <br>[15] Shi, C.; Tan, C.;Wang, T.; Wang, L. A Waste Classification Method Based on a Multilayer Hybrid Convolution Neural Network. Appl. Sci.2021, 11, 8572. <br>[16] Ren, C.; Jung, H.; Lee, S.; Jeong, D. Coastal Waste Detection Based on Deep Convolutional Neural Networks. Sensors 2021, 21, 7269. <br>[17] Kumsetty, N.; Nekkare, A. TrashBox database, doi: 10.5281/zenodo.1234. <br>[18] Bobulski, J.; Kubanek M. Deep Learning for Plastic Waste Classification System. Applied Computational Intelligence and Soft Computing, 2021, art. no. 6626948. </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); });*/ jQuery.get({ url: "https://publications.waset.org/xhr/user-menu", cache: false }).then(function(response){ jQuery('#mainNavMenu').append(response); }); }); </script> </body> </html>

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Analysis of Histogram Asymmetry for Waste Recognition