{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T07:11:06Z","timestamp":1769757066797,"version":"3.49.0"},"reference-count":28,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2016,2,22]],"date-time":"2016-02-22T00:00:00Z","timestamp":1456099200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>A novel local structure descriptor (LSD) for color image retrieval is proposed in this paper. Local structures are defined based on a similarity of edge orientation, and LSD is constructed using the underlying colors in local structures with similar edge direction. LSD can effectively combine color, texture and shape as a whole for image retrieval. LSH integrates the advantages of both statistical and structural texture description methods, and it possesses high indexing capability and low dimensionality. In addition, the proposed feature extraction algorithm does not need to train on a large scale training datasets, and it can extract local structure histogram based on LSD. The experimental results on the Corel image databases show that the descriptor has a better image retrieval performance than other descriptors.<\/jats:p>","DOI":"10.3390\/info7010009","type":"journal-article","created":{"date-parts":[[2016,2,22]],"date-time":"2016-02-22T10:24:17Z","timestamp":1456136657000},"page":"9","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["A Novel Local Structure Descriptor for Color Image Retrieval"],"prefix":"10.3390","volume":"7","author":[{"given":"Zhiyong","family":"Zeng","sequence":"first","affiliation":[{"name":"Faculty of Software, Fujian Normal University, Qishan Community, Fuzhou 350108, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,2,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.patcog.2006.04.045","article-title":"A survey of content-based image retrieval with high-level semantics","volume":"40","author":"Liu","year":"2007","journal-title":"Pattern Recognit."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.patcog.2011.05.013","article-title":"A review on automatic image annotation techniques","volume":"45","author":"Zhang","year":"2012","journal-title":"Pattern Recognit."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1245","DOI":"10.1098\/rstb.1998.0280","article-title":"Visual attention mediated by biased competition in extrastriate visual cortex","volume":"353","author":"Desimone","year":"1998","journal-title":"Philos. 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