{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T08:43:44Z","timestamp":1742978624464,"version":"3.40.3"},"publisher-location":"Cham","reference-count":30,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030588168"},{"type":"electronic","value":"9783030588175"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-58817-5_54","type":"book-chapter","created":{"date-parts":[[2020,9,29]],"date-time":"2020-09-29T15:03:56Z","timestamp":1601391836000},"page":"753-770","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A Novel Feature Extractor Based on the Modified Approach of Histogram of Oriented Gradient"],"prefix":"10.1007","author":[{"given":"Shaveta","family":"Malik","sequence":"first","affiliation":[]},{"given":"Archana","family":"Mire","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2657-8700","authenticated-orcid":false,"given":"Amit Kumar","family":"Tyagi","sequence":"additional","affiliation":[]},{"given":"Vasudha","family":"Arora","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,30]]},"reference":[{"key":"54_CR1","unstructured":"kumar Pagrut, N., Ganguly, S., Jaiswal, V., Singh, C.: An overview on epizootic ulcerative syndrome of fishes in India: a comprehensive report. J. Entomol. Zool. Stud. 11(4), 1941\u20131943 (2017)"},{"issue":"7","key":"54_CR2","first-page":"13255","volume":"4","author":"AJ Suresh","year":"2016","unstructured":"Suresh, A.J., Asha, P.: Human action recognition in video using histogram of oriented gradient (HOG) features and probabilistic neural network (PNN). Int. J. Innov. Res. Comput. Commun. Eng. 4(7), 13255\u201313263 (2016)","journal-title":"Int. J. Innov. Res. Comput. Commun. Eng."},{"key":"54_CR3","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1146\/annurev-marine-010213-135029","volume":"6","author":"CA Burge","year":"2014","unstructured":"Burge, C.A., et al.: Climate change influences on marine infectious diseases: implications for management and society. Ann. Rev. Mar. Sci. 6, 249\u2013277 (2014)","journal-title":"Ann. Rev. Mar. Sci."},{"key":"54_CR4","doi-asserted-by":"publisher","first-page":"471","DOI":"10.1146\/annurev-marine-010814-015646","volume":"7","author":"KD Lafferty","year":"2015","unstructured":"Lafferty, K.D., et al.: Infectious diseases affect marine fisheries and aquaculture economics. Ann. Rev. Mar. Sci. 7, 471\u2013496 (2015)","journal-title":"Ann. Rev. Mar. Sci."},{"key":"54_CR5","doi-asserted-by":"crossref","unstructured":"Malik, S., Kumar, T., Sahoo, A.K.: Image processing techniques for identification of fish disease. In: IEEE 2nd International Conference on Signal and Image Processing (ICSIP), pp. 55\u201359 (2017)","DOI":"10.1109\/SIPROCESS.2017.8124505"},{"key":"54_CR6","unstructured":"Antony Seba1, P., Rama Subbu Laskhmi, S., Umamaheswari, P.: Fish recognition based on HOG feature extraction using SVM prediction. Int. J. Adv. Res. Comput. Commun. Eng. 6(5), 296\u2013299 (2017)"},{"key":"54_CR7","unstructured":"Ansari, F.J.: Hand gesture recognition using fusion of SIFT and HoG with SVM as a classifier. Int. J. Eng. Technol. Sci. Res. IJETSR 4(9), 206\u2013210 (2017)"},{"key":"54_CR8","unstructured":"Maity, U., Mukherjee, J.: Automated color logo recognition technique using color and hog features. Int. J. Comput. Appl. 170(2), 38\u201341 (2017)"},{"issue":"2","key":"54_CR9","first-page":"21","volume":"9","author":"HA Khan","year":"2017","unstructured":"Khan, H.A.: MCS HOG features and SVM based handwritten digit recognition system. J. Intell. Learn. Syst. Appl. 9(2), 21\u201333 (2017)","journal-title":"J. Intell. Learn. Syst. Appl."},{"issue":"3","key":"54_CR10","first-page":"206","volume":"7","author":"UM Babri","year":"2016","unstructured":"Babri, U.M., Tanvir, M., Khurshid, K.: Feature based correspondence: a comparative study on image matching algorithms. Int. J. Adv. Comput. Sci. Appl. 7(3), 206\u2013210 (2016)","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"54_CR11","doi-asserted-by":"crossref","unstructured":"Dalal, N., Triggs, B., Schmid, C.: Human detection using oriented histograms of flow and appearance. In: ECCV 2006, pp. 428\u2013441 (2010)","DOI":"10.1007\/11744047_33"},{"key":"54_CR12","doi-asserted-by":"crossref","unstructured":"Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), pp. 886\u2013893 (2005)","DOI":"10.1109\/CVPR.2005.177"},{"issue":"6","key":"54_CR13","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1145\/358669.358692","volume":"24","author":"MA Fischler","year":"1981","unstructured":"Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381\u2013395 (1981)","journal-title":"Commun. ACM"},{"issue":"2","key":"54_CR14","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/j.eij.2015.05.002","volume":"16","author":"A Haiam","year":"2015","unstructured":"Haiam, A., Abdul-Azim, H.A.: Human action recognition using trajectory based representation. Egypt. Inform. J. 16(2), 187\u2013198 (2015)","journal-title":"Egypt. Inform. J."},{"issue":"4","key":"54_CR15","first-page":"381","volume":"5","author":"G Pooja","year":"2016","unstructured":"Pooja, G., Revansiddappa, S.K.: Abnormal activity detection using HOG features and SVM classifier. Int. J. Adv. Res. Electr. Electron. Instrum. Eng. 5(4), 381\u2013395 (2016)","journal-title":"Int. J. Adv. Res. Electr. Electron. Instrum. Eng."},{"key":"54_CR16","first-page":"1","volume":"2015","author":"E Adetiba","year":"2015","unstructured":"Adetiba, E., Olugbara, O.O.: Lung cancer prediction using neural network ensemble with histogram of oriented gradient genomic features. Sci. J. 2015, 1\u201317 (2015)","journal-title":"Sci. J."},{"key":"54_CR17","doi-asserted-by":"crossref","unstructured":"Tian, S., Lu, S., Su, B., Tan, C.L.: Scene text recognition using co-occurrence of histogram of oriented gradients. In: Proceedings of the 2013 12th International Conference on Document Analysis and Recognition, Washington, DC, USA, pp. 912\u2013916 (2013)","DOI":"10.1109\/ICDAR.2013.186"},{"issue":"3","key":"54_CR18","first-page":"48","volume":"7","author":"N Bagum","year":"2013","unstructured":"Bagum, N., Monir, M.S.: Present status of fish disease and economic losses due to incidence of disease in rural freshwater aquaculture. J. Innov. Dev. Strateg. (JIDS) 7(3), 48\u201353 (2013)","journal-title":"J. Innov. Dev. Strateg. (JIDS)"},{"issue":"7","key":"54_CR19","first-page":"79","volume":"6","author":"V Lyubchenko","year":"2016","unstructured":"Lyubchenko, V., Matarneh, R., Kobylin, O.: Digital image processing techniques for detection and diagnosis of fish diseases. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 6(7), 79\u201383 (2016)","journal-title":"Int. J. Adv. Res. Comput. Sci. Softw. Eng."},{"issue":"4","key":"54_CR20","doi-asserted-by":"publisher","first-page":"342","DOI":"10.1080\/23308249.2016.1193841","volume":"24","author":"V Kumar","year":"2016","unstructured":"Kumar, V., Roy, S., Meena, D.K., Sarkar, U.K.: Application of probiotics in shrimp aquaculture: importance, mechanisms of action, and methods of administration. Rev. Fish. Sci. Aquac. 24(4), 342\u2013368 (2016)","journal-title":"Rev. Fish. Sci. Aquac."},{"issue":"1","key":"54_CR21","doi-asserted-by":"publisher","first-page":"49","DOI":"10.14738\/aivp.51.2809","volume":"5","author":"S Malik","year":"2017","unstructured":"Malik, S., Kumar, T., Sahoo, A.K.: A novel approach to fish disease diagnostic system based on machine learning. Adv. Image Video Process. 5(1), 49\u201357 (2017)","journal-title":"Adv. Image Video Process."},{"issue":"7","key":"54_CR22","first-page":"6","volume":"135","author":"TK ShavetaMalik","year":"2016","unstructured":"ShavetaMalik, T.K.: Various edge detection techniques on different categories of fish. Int. J. Comput. Appl. 135(7), 6\u201311 (2016)","journal-title":"Int. J. Comput. Appl."},{"issue":"5","key":"54_CR23","first-page":"216","volume":"15","author":"S Malik","year":"2017","unstructured":"Malik, S., Kumar, T., Sahoo, A.K.: Fish disease detection using HOG and FAST feature descriptor. Int. J. Comput. Sci. Inf. Secur. (IJCSIS) 15(5), 216\u2013221 (2017)","journal-title":"Int. J. Comput. Sci. Inf. Secur. (IJCSIS)"},{"key":"54_CR24","doi-asserted-by":"crossref","unstructured":"Cai, Z., Yu, P., Liang, Y., Lin, B., Huang, H.: SVM-KNN algorithm for image classification based on enhanced HOG feature. In: Proceedings of the International Conference on Intelligent systems and Image Processing (2016)","DOI":"10.12792\/icisip2016.023"},{"issue":"7","key":"54_CR25","first-page":"50","volume":"6","author":"XA Stella","year":"2016","unstructured":"Stella, X.A., Sujatha, N.: Performance analysis of GFE, HOG and LBP feature extraction techniques using kNN classifier for oral cancer detection. J. Netw. Commun. Emerg. 6(7), 50\u201356 (2016)","journal-title":"J. Netw. Commun. Emerg."},{"key":"54_CR26","unstructured":"Niblack, W.: An Introduction to Digital Image Processing. Strandberg Publishing Company (1985)"},{"key":"54_CR27","unstructured":"Antony Seba, P., et al.: Fish recognition based on HOG feature extraction using SVM prediction. Int. J. Adv. Res. Comput. Commun. Eng. 6(5), 296\u2013299 (2017)"},{"issue":"1","key":"54_CR28","first-page":"322","volume":"9","author":"AK Santra","year":"2012","unstructured":"Santra, A.K., Christy, C.J.: Genetic algorithm and confusion matrix for document clustering. IJCSI Int. J. Comput. Sci. Issues 9(1), 322 (2012)","journal-title":"IJCSI Int. J. Comput. Sci. Issues"},{"issue":"1","key":"54_CR29","first-page":"37","volume":"2","author":"DMW Powers","year":"2011","unstructured":"Powers, D.M.W.: Evaluation: from precision, recall and F-measure to ROC: informedness, markendness & correlation. J. Mach. Learn. Technol. 2(1), 37\u201363 (2011)","journal-title":"J. Mach. Learn. Technol."},{"issue":"6","key":"54_CR30","first-page":"68","volume":"8","author":"JNS Lopes","year":"2011","unstructured":"Lopes, J.N.S., Gon\u00e7alves, A.N.A., Fujimoto, R.Y., Carvalho, J.C.C.: Diagnosis of fish diseases using artificial neural networks. IJCSI Int. J. Comput. Sci. Issues 8(6), 68\u201373 (2011)","journal-title":"IJCSI Int. J. Comput. Sci. Issues"}],"container-title":["Lecture Notes in Computer Science","Computational Science and Its Applications \u2013 ICCSA 2020"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-58817-5_54","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,15]],"date-time":"2024-08-15T03:04:47Z","timestamp":1723691087000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-58817-5_54"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030588168","9783030588175"],"references-count":30,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-58817-5_54","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"30 September 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCSA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Science and Its Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cagliari","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 July 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 July 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccsa2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.iccsa.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Cyber chair 4","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1450","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"466","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"32","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"32% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.5","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Conference was held virtually due to COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}