{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T22:39:02Z","timestamp":1761863942553,"version":"build-2065373602"},"reference-count":62,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2019,3,1]],"date-time":"2019-03-01T00:00:00Z","timestamp":1551398400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Spanish Government","award":["DPI2012-36166","AP2010-0947"],"award-info":[{"award-number":["DPI2012-36166","AP2010-0947"]}]},{"DOI":"10.13039\/501100013410","name":"INCIBE","doi-asserted-by":"publisher","award":["INCIBEI-2015-27359","Addendum 22","Addendum 01"],"award-info":[{"award-number":["INCIBEI-2015-27359","Addendum 22","Addendum 01"]}],"id":[{"id":"10.13039\/501100013410","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents a new texture descriptor booster, Complete Local Oriented Statistical Information Booster (CLOSIB), based on statistical information of the image. Our proposal uses the statistical information of the texture provided by the image gray-levels differences to increase the discriminative capability of Local Binary Patterns (LBP)-based and other texture descriptors. We demonstrated that Half-CLOSIB and M-CLOSIB versions are more efficient and precise than the general one. H-CLOSIB may eliminate redundant statistical information and the multi-scale version, M-CLOSIB, is more robust. We evaluated our method using four datasets: KTH TIPS (2-a) for material recognition, UIUC and USPTex for general texture recognition and JAFFE for face recognition. The results show that when we combine CLOSIB with well-known LBP-based descriptors, the hit rate increases in all the cases, introducing in this way the idea that CLOSIB can be used to enhance the description of texture in a significant number of situations. Additionally, a comparison with recent algorithms demonstrates that a combination of LBP methods with CLOSIB variants obtains comparable results to those of the state-of-the-art.<\/jats:p>","DOI":"10.3390\/s19051048","type":"journal-article","created":{"date-parts":[[2019,3,4]],"date-time":"2019-03-04T05:45:36Z","timestamp":1551678336000},"page":"1048","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Boosting Texture-Based Classification by Describing Statistical Information of Gray-Levels Differences"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7540-2985","authenticated-orcid":false,"given":"\u00d3scar","family":"Garc\u00eda-Olalla","sequence":"first","affiliation":[{"name":"Department of Electrical, Systems and Automation, Universidad de Le\u00f3n, 24007 Le\u00f3n, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6573-8477","authenticated-orcid":false,"given":"Laura","family":"Fern\u00e1ndez-Robles","sequence":"additional","affiliation":[{"name":"Department of Mechanical, Computer Science and Aerospace Engineering, Universidad de Le\u00f3n, 24007 Le\u00f3n, Spain"},{"name":"Spanish National Cybersecurity Institute (INCIBE), 24005 Le\u00f3n, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2081-774X","authenticated-orcid":false,"given":"Enrique","family":"Alegre","sequence":"additional","affiliation":[{"name":"Department of Electrical, Systems and Automation, Universidad de Le\u00f3n, 24007 Le\u00f3n, Spain"},{"name":"Spanish National Cybersecurity Institute (INCIBE), 24005 Le\u00f3n, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5152-4555","authenticated-orcid":false,"given":"Manuel","family":"Castej\u00f3n-Limas","sequence":"additional","affiliation":[{"name":"Department of Mechanical, Computer Science and Aerospace Engineering, Universidad de Le\u00f3n, 24007 Le\u00f3n, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1202-5232","authenticated-orcid":false,"given":"Eduardo","family":"Fidalgo","sequence":"additional","affiliation":[{"name":"Department of Electrical, Systems and Automation, Universidad de Le\u00f3n, 24007 Le\u00f3n, Spain"},{"name":"Spanish National Cybersecurity Institute (INCIBE), 24005 Le\u00f3n, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"44876","DOI":"10.1109\/ACCESS.2018.2864754","article-title":"TCvBsISM: Texture Classification via B-Splines-Based Image Statistical Modeling","volume":"6","author":"Liu","year":"2018","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2007","DOI":"10.1016\/j.patrec.2013.02.009","article-title":"Texture databases\u2014A comprehensive survey","volume":"34","author":"Hossain","year":"2013","journal-title":"Pattern Recognit. 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