{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:42:58Z","timestamp":1742913778975,"version":"3.40.3"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030959029"},{"type":"electronic","value":"9783030959036"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-030-95903-6_46","type":"book-chapter","created":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T13:03:32Z","timestamp":1643720612000},"page":"445-457","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Identifying Vehicle Exterior Color by Image Processing and Deep Learning"],"prefix":"10.1007","author":[{"given":"Somayeh","family":"Abniki","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kin Fun","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tom","family":"Avant","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,2,2]]},"reference":[{"key":"46_CR1","doi-asserted-by":"publisher","unstructured":"Aarathi, K.S., Abraham, A.: Vehicle color recognition using deep learning for hazy images. In: International Conference on Inventive Communication and Computational Technologies (ICICCT), pp. 335\u2013339 (2017). https:\/\/doi.org\/10.1109\/ICICCT.2017.7975215","DOI":"10.1109\/ICICCT.2017.7975215"},{"key":"46_CR2","doi-asserted-by":"publisher","unstructured":"Chen, P., Bai, X., Liu, W.: Vehicle color recognition on urban road by feature context. IEEE Trans. Intell. Transp. Sys. 15(5), 2340\u20132346 (2014). https:\/\/doi.org\/10.1109\/TITS.2014.2308897","DOI":"10.1109\/TITS.2014.2308897"},{"key":"46_CR3","doi-asserted-by":"publisher","unstructured":"Li, X., et al.: Vehicle color recognition using vector matching of template. In: 3rd International Symposium on Electronic Commerce and Security, pp. 189\u2013193 (2010). https:\/\/doi.org\/10.1109\/ISECS.2010.50","DOI":"10.1109\/ISECS.2010.50"},{"key":"46_CR4","unstructured":"Rachmadi, R.F., Purnama, I.: Vehicle color recognition using convolutional neural network. http:\/\/arxiv.org\/abs\/1510.07391"},{"key":"46_CR5","doi-asserted-by":"publisher","unstructured":"Shobha, R.B.R.: Classification of vehicles using image processing techniques. Int. J. Recent Trends Eng. Res. 4(3) 393\u2013401 (2018). https:\/\/doi.org\/10.23883\/ijrter.2018.4144.qcmco","DOI":"10.23883\/ijrter.2018.4144.qcmco"},{"key":"46_CR6","doi-asserted-by":"publisher","unstructured":"Tilakaratna, D.S.B., Watchareeruetai, U., Siddhichai, S., Natcharapinchai, N.: Image analysis algorithms for vehicle color recognition. In: International Electrical Engineering Congress, pp. 4\u20137 (2017). https:\/\/doi.org\/10.1109\/IEECON.2017.807588","DOI":"10.1109\/IEECON.2017.807588"},{"issue":"3","key":"46_CR7","doi-asserted-by":"publisher","first-page":"850","DOI":"10.1109\/TIP.2007.891147","volume":"16","author":"LW Tsai","year":"2007","unstructured":"Tsai, L.W., Hsieh, J.W., Fan, K.C.: Vehicle detection using normalized color and edge map. IEEE Tran. Image Process. 16(3), 850\u2013864 (2007). https:\/\/doi.org\/10.1109\/TIP.2007.891147","journal-title":"IEEE Tran. Image Process."},{"key":"46_CR8","unstructured":"Dule, E., G\u00f6kmen, M., Berato\u01e7lu, M.S.: A convenient feature vector construction for vehicle color recognition. In: 11th WSEAS International Conference on Neural Networks, pp. 250\u2013255 (2010)"},{"key":"46_CR9","doi-asserted-by":"crossref","unstructured":"He, K., Sun, J., Tang, X.: Single image haze removal using dark channel prior. IEEE Trans. Pattern Anal. Mach. Intell. 33(12) (2011)","DOI":"10.1109\/TPAMI.2010.168"},{"key":"46_CR10","unstructured":"Gonzalez, R.C., Woods, R.E., Eddis, S.L.: Digital Image Processing Using MATLAB, 2nd edn. Tata McGraw Hill, New York (2010)"},{"key":"46_CR11","doi-asserted-by":"publisher","first-page":"1871","DOI":"10.1145\/1390681.1442794","volume":"9","author":"R-E Fan","year":"2008","unstructured":"Fan, R.-E., et al.: LIBLINEAR: a library for large linear classification. J. Mach. Learn. Res. 9, 1871\u20131874 (2008). https:\/\/doi.org\/10.1145\/1390681.1442794","journal-title":"J. Mach. Learn. Res."},{"key":"46_CR12","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1145\/3065386","volume":"60","author":"A Krizhevsky","year":"2012","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. Commun. ACM 60, 84\u201390 (2012)","journal-title":"Commun. ACM"},{"issue":"2","key":"46_CR13","doi-asserted-by":"publisher","first-page":"971","DOI":"10.1109\/JSEN.2014.2358079","volume":"15","author":"JW Hsieh","year":"2015","unstructured":"Hsieh, J.W., et al.: Vehicle color classification under different lighting conditions through color correction. IEEE Sens. J. 15(2), 971\u2013983 (2015). https:\/\/doi.org\/10.1109\/JSEN.2014.2358079","journal-title":"IEEE Sens. J."},{"issue":"5","key":"46_CR14","doi-asserted-by":"publisher","first-page":"2925","DOI":"10.1109\/TITS.2015.2430892","volume":"16","author":"C Hu","year":"2015","unstructured":"Hu, C., et al.: Vehicle color recognition with spatial pyramid deep learning. IEEE Trans. Intell. Trans. Sys. 16(5), 2925\u20132934 (2015). https:\/\/doi.org\/10.1109\/TITS.2015.2430892","journal-title":"IEEE Trans. Intell. Trans. Sys."},{"key":"46_CR15","doi-asserted-by":"publisher","unstructured":"Kim, K.J., Park, S.M., Choi, Y.J.: Deciding the number of color histogram bins for vehicle color recognition. In: 3rd IEEE Asia-Pacific Services Computing Conference, pp. 134\u2013138 (2008). https:\/\/doi.org\/10.1109\/APSCC.2008.207","DOI":"10.1109\/APSCC.2008.207"},{"issue":"16","key":"46_CR16","doi-asserted-by":"publisher","first-page":"20889","DOI":"10.1007\/s11042-017-5429-8","volume":"77","author":"K Chowdhury","year":"2017","unstructured":"Chowdhury, K., Chaudhuri, D., Pal, A.K.: A new image segmentation technique using bi-entropy function minimization. Multimedia Tools Appl. 77(16), 20889\u201320915 (2017). https:\/\/doi.org\/10.1007\/s11042-017-5429-8","journal-title":"Multimedia Tools Appl."},{"key":"46_CR17","doi-asserted-by":"publisher","unstructured":"Sen, H., Agarwal, A.: A comparative analysis of entropy based segmentation with Otsu method for gray and color images. In: International conference of Electronics, Communication and Aerospace Technology, vol. 2017, pp. 113\u2013118, January 2017. https:\/\/doi.org\/10.1109\/ICECA.2017.8203655","DOI":"10.1109\/ICECA.2017.8203655"},{"key":"46_CR18","doi-asserted-by":"crossref","unstructured":"Zhang, H., Fritts, J.E., Goldman, S.A.: An entropy-based objective evaluation method for image segmentation. Int. Soc. Opt. Eng. 38\u201349 (2004)","DOI":"10.1117\/12.527167"},{"issue":"3","key":"46_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pone.0229651","volume":"15","author":"W Yang","year":"2020","unstructured":"Yang, W., Cai, L., Wu, F.: Image segmentation based on gray level and local relative entropy two dimensional histogram. PLoS ONE 15(3), 1\u20139 (2020). https:\/\/doi.org\/10.1371\/journal.pone.0229651","journal-title":"PLoS ONE"},{"key":"46_CR20","doi-asserted-by":"publisher","unstructured":"Pauzi, G.A.: Colour classification using entropy algorithm in real time colour recognition system for blindness people. KnE Eng. 1(1), 0\u20135 (2016). https:\/\/doi.org\/10.18502\/keg.v0i0.485","DOI":"10.18502\/keg.v0i0.485"},{"key":"46_CR21","unstructured":"Bochkovskiy, A., Wang, C.-Y., Liao, H.-Y.M.: YOLOv4: optimal speed and accuracy of object detection (2020). https:\/\/arxiv.org\/abs\/2004.10934"},{"key":"46_CR22","unstructured":"Ponnusamy, A.: cvlib-high level computer vision library for Python (2018). https:\/\/www.cvlib.net\/"},{"key":"46_CR23","doi-asserted-by":"publisher","unstructured":"AlSaeed, D.H., El-Zaart, A., Bouridane, A.: Minimum cross entropy thresholding using entropy-Li based on log-normal distribution for skin cancer images. In: 7th International Conference on Signal Image Technology & Internet-Based Systems, pp. 426\u2013430 (2011). https:\/\/doi.org\/10.1109\/SITIS.2011.86","DOI":"10.1109\/SITIS.2011.86"},{"key":"46_CR24","unstructured":"Mars, W.: Martian Colour Wheel. https:\/\/warrenmars.com"}],"container-title":["Lecture Notes on Data Engineering and Communications Technologies","Advances in Internet, Data & Web Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-95903-6_46","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,17]],"date-time":"2024-09-17T18:32:41Z","timestamp":1726597961000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-95903-6_46"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030959029","9783030959036"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-95903-6_46","relation":{},"ISSN":["2367-4512","2367-4520"],"issn-type":[{"type":"print","value":"2367-4512"},{"type":"electronic","value":"2367-4520"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"2 February 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EIDWT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Emerging Internetworking, Data & Web Technologies","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Okayama","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 February 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 February 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eidwt2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}