{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T22:43:04Z","timestamp":1760395384843,"version":"build-2065373602"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030606381"},{"type":"electronic","value":"9783030606398"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-60639-8_51","type":"book-chapter","created":{"date-parts":[[2020,10,14]],"date-time":"2020-10-14T10:04:02Z","timestamp":1602669842000},"page":"614-625","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Feature Selection and Classification of Texture Images Based on Local Structure and Low-Rank Constraints"],"prefix":"10.1007","author":[{"given":"Rihong","family":"Li","sequence":"first","affiliation":[]},{"given":"Hongxia","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Jiaxiang","family":"Luo","sequence":"additional","affiliation":[]},{"given":"Haiming","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Weipeng","family":"Yang","sequence":"additional","affiliation":[]},{"given":"An","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,10,15]]},"reference":[{"issue":"7","key":"51_CR1","doi-asserted-by":"publisher","first-page":"971","DOI":"10.1109\/TPAMI.2002.1017623","volume":"24","author":"T Ojala","year":"2002","unstructured":"Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 971\u2013987 (2002)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"6","key":"51_CR2","doi-asserted-by":"publisher","first-page":"1657","DOI":"10.1109\/TIP.2010.2044957","volume":"19","author":"Z Guo","year":"2010","unstructured":"Guo, Z., Zhang, L., Zhang, D.: A completed modeling of local binary pattern operator for texture classification. IEEE Trans. Image Process. 19(6), 1657\u20131663 (2010)","journal-title":"IEEE Trans. Image Process."},{"key":"51_CR3","doi-asserted-by":"crossref","unstructured":"Sifre, L., Mallat, S.: Rotation, scaling and deformation invariant scattering for texture discrimination. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1233\u20131240 (2013)","DOI":"10.1109\/CVPR.2013.163"},{"key":"51_CR4","doi-asserted-by":"crossref","unstructured":"Zhang, L., Zhou, Z., Li, H.: Binary gabor pattern: an efficient and robust descriptor for texture classification. In: 19th IEEE International Conference on Image Processing, pp. 81\u201384 (2012)","DOI":"10.1109\/ICIP.2012.6466800"},{"issue":"8","key":"51_CR5","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1016\/j.imavis.2012.04.001","volume":"30","author":"E Rahtu","year":"2012","unstructured":"Rahtu, E., Heikkil\u00e4, J., Ojansivu, V., et al.: Local phase quantization for blur-insensitive image analysis. Image Vis. Comput. 30(8), 501\u2013512 (2012)","journal-title":"Image Vis. Comput."},{"key":"51_CR6","unstructured":"Kannala, J., Rahtu, E.: Bsif: binarized statistical image features. In: Proceedings of the 21st International Conference on Pattern Recognition, pp. 1363\u20131366 (2012)"},{"key":"51_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1007\/978-3-540-75690-3_18","volume-title":"Analysis and Modeling of Faces and Gestures","author":"X Tan","year":"2007","unstructured":"Tan, X., Triggs, B.: Fusing gabor and LBP feature sets for kernel-based face recognition. In: Zhou, S.K., Zhao, W., Tang, X., Gong, S. (eds.) AMFG 2007. LNCS, vol. 4778, pp. 235\u2013249. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-75690-3_18"},{"key":"51_CR8","unstructured":"Liu, G., Lin, Z., Yu, Y.: Robust subspace segmentation by low-rank representation. In: Proceedings of the 27th International Conference on Machine Learning, pp. 663\u2013670 (2010)"},{"issue":"6","key":"51_CR9","doi-asserted-by":"crossref","first-page":"1083","DOI":"10.1109\/TNNLS.2013.2287275","volume":"25","author":"X Liu","year":"2013","unstructured":"Liu, X., Wang, L., Zhang, J., et al.: Global and local structure preservation for feature selection. IEEE Trans. Neural Networks Learn. Syst. 25(6), 1083\u20131095 (2013)","journal-title":"IEEE Trans. Neural Networks Learn. Syst."},{"key":"51_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"716","DOI":"10.1007\/978-3-642-33709-3_51","volume-title":"Computer Vision\u2013ECCV 2012","author":"S ul Hussain","year":"2012","unstructured":"ul Hussain, S., Triggs, B.: Visual recognition using local quantized patterns. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7573, pp. 716\u2013729. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33709-3_51"},{"key":"51_CR11","doi-asserted-by":"crossref","unstructured":"Li, M., et al.: Head-shoulder based gender recognition. In: 2013 IEEE International Conference on Image Processing, pp. 2753\u20132756 (2013)","DOI":"10.1109\/ICIP.2013.6738567"},{"key":"51_CR12","unstructured":"He, X., Cai, D., Niyogi, P.: Laplacian score for feature selection. In: Advances in Neural Information Processing Systems, pp. 507\u2013514 (2006)"},{"key":"51_CR13","doi-asserted-by":"crossref","unstructured":"Cai, D., Zhang, C., He, X.: Unsupervised feature selection for multi-cluster data. In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 333\u2013342 (2010)","DOI":"10.1145\/1835804.1835848"},{"key":"51_CR14","doi-asserted-by":"crossref","unstructured":"Guo, J., et al.: Unsupervised feature selection with ordinal locality. In: 2017 IEEE International Conference on Multimedia and Expo, pp. 1213\u20131218 (2017)","DOI":"10.1109\/ICME.2017.8019357"},{"key":"51_CR15","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.patrec.2014.07.020","volume":"51","author":"FS Khan","year":"2015","unstructured":"Khan, F.S., Anwer, R.M., van de Weijer, J., et al.: Compact color\u2013texture description for texture classification. Pattern Recogn. Lett. 51, 16\u201322 (2015)","journal-title":"Pattern Recogn. Lett."},{"issue":"1\u20132","key":"51_CR16","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1007\/s11263-005-4635-4","volume":"62","author":"M Varma","year":"2005","unstructured":"Varma, M., Zisserman, A.: A statistical approach to texture classification from single images. Int. J. Comput. Vis. 62(1\u20132), 61\u201381 (2005)","journal-title":"Int. J. Comput. Vis."},{"key":"51_CR17","doi-asserted-by":"crossref","unstructured":"Liu, G., Yan, S.: Latent low-rank representation for subspace segmentation and feature extraction. In: 2011 International Conference on Computer Vision, pp. 1615\u20131622 (2011)","DOI":"10.1109\/ICCV.2011.6126422"},{"key":"51_CR18","doi-asserted-by":"crossref","unstructured":"Du, L., Shen, Y.D.: Unsupervised feature selection with adaptive structure learning. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 209\u2013218 (2015)","DOI":"10.1145\/2783258.2783345"},{"key":"51_CR19","unstructured":"Mallikarjuna, P., et al.: The kth-tips2 database. KTH Royal Institute of Technology (2006)"},{"key":"51_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1007\/978-3-540-24673-2_21","volume-title":"Computer Vision-ECCV 2004","author":"E Hayman","year":"2004","unstructured":"Hayman, E., Caputo, B., Fritz, M., Eklundh, J.-O.: On the significance of real-world conditions for material classification. In: Pajdla, T., Matas, J. (eds.) ECCV 2004. LNCS, vol. 3024, pp. 253\u2013266. Springer, Heidelberg (2004). https:\/\/doi.org\/10.1007\/978-3-540-24673-2_21"},{"key":"51_CR21","doi-asserted-by":"crossref","unstructured":"Caputo, B., Hayman, E., Mallikarjuna, P.: Class-specific material categorization. In: Tenth IEEE International Conference on Computer Vision, pp. 1597\u20131604 (2005)","DOI":"10.1109\/ICCV.2005.54"},{"issue":"3","key":"51_CR22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1961189.1961199","volume":"2","author":"CC Chang","year":"2011","unstructured":"Chang, C.C., Lin, C.J.: LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. 2(3), 1\u201327 (2011)","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"51_CR23","unstructured":"Hall, M.A.: Correlation-based feature selection of discrete and numeric class machine learning (2000)"},{"key":"51_CR24","unstructured":"Yang, Y., et al.: L2, 1-norm regularized discriminative feature selection for unsupervised. In: Twenty-Second International Joint Conference on Artificial Intelligence (2011)"},{"issue":"3","key":"51_CR25","doi-asserted-by":"publisher","first-page":"574","DOI":"10.1109\/TPAMI.2011.145","volume":"34","author":"L Liu","year":"2012","unstructured":"Liu, L., Fieguth, P.: Texture classification from random features. IEEE Trans. Pattern Anal. Mach. Intell. 34(3), 574\u2013586 (2012)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"4","key":"51_CR26","doi-asserted-by":"publisher","first-page":"1604","DOI":"10.1109\/TIP.2016.2526898","volume":"25","author":"R Mehta","year":"2016","unstructured":"Mehta, R., Eguiazarian, K.E.: Texture classification using dense micro-block difference. IEEE Trans. Image Process. 25(4), 1604\u20131616 (2016)","journal-title":"IEEE Trans. Image Process."},{"key":"51_CR27","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-642-33786-4_1","volume-title":"Computer Vision\u2013ECCV 2012","author":"G Sharma","year":"2012","unstructured":"Sharma, G., ul Hussain, S., Jurie, F.: Local Higher-Order Statistics (LHS) for texture categorization and facial analysis. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7578, pp. 1\u201312. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33786-4_1"},{"issue":"6","key":"51_CR28","doi-asserted-by":"publisher","first-page":"2557","DOI":"10.1109\/TIP.2014.2316640","volume":"23","author":"X Hong","year":"2014","unstructured":"Hong, X., Zhao, G., Pietik\u00e4inen, M., et al.: Combining LBP difference and feature correlation for texture description. IEEE Trans. Image Process. 23(6), 2557\u20132568 (2014)","journal-title":"IEEE Trans. Image Process."},{"issue":"7","key":"51_CR29","doi-asserted-by":"publisher","first-page":"2254","DOI":"10.1109\/TIP.2015.2419081","volume":"24","author":"J Ryu","year":"2015","unstructured":"Ryu, J., Hong, S., Yang, H.S.: Sorted consecutive local binary pattern for texture classification. IEEE Trans. Image Process. 24(7), 2254\u20132265 (2015)","journal-title":"IEEE Trans. Image Process."},{"issue":"4","key":"51_CR30","doi-asserted-by":"publisher","first-page":"880","DOI":"10.1109\/TMM.2017.2760102","volume":"20","author":"W Zhang","year":"2017","unstructured":"Zhang, W., Zhang, W., Liu, K., et al.: A feature descriptor based on local normalized difference for real-world texture classification. IEEE Trans. Multimedia 20(4), 880\u2013888 (2017)","journal-title":"IEEE Trans. Multimedia"},{"issue":"7","key":"51_CR31","doi-asserted-by":"publisher","first-page":"382","DOI":"10.1049\/el.2018.7631","volume":"55","author":"SK Roy","year":"2019","unstructured":"Roy, S.K., Dubey, S.R., Chaudhuri, B.B.: Local ZigZag Max histograms of pooling pattern for texture classification. Electron. Lett. 55(7), 382\u2013384 (2019)","journal-title":"Electron. Lett."}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-60639-8_51","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T22:03:55Z","timestamp":1760393035000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-60639-8_51"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030606381","9783030606398"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-60639-8_51","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":"15 October 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Nanjing","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"16 October 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.prcv.cn\/index_en.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft CMT system","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"402","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":"158","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":"0","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":"39% - 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":"3","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":"4","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}