{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T06:43:33Z","timestamp":1740120213468,"version":"3.37.3"},"reference-count":16,"publisher":"World Scientific Pub Co Pte Ltd","issue":"03","funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["BK20131090","2011-wlw-005","61301186"],"award-info":[{"award-number":["BK20131090","2011-wlw-005","61301186"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2017,3]]},"abstract":"<jats:p> In this paper, we propose a gray-scale texture descriptor, name the global and local oriented edge magnitude patterns (GLOEMP), for texture classification. GLOEMP is a framework, which is able to effectively combine local texture, global structure information and contrast of texture images. In GLOEMP, the principal orientation is determined by Histogram of Gradient (HOG) feature, then each direction is respectively shown in detail by a local binary patterns (LBP) occurrence histogram. Due to the fact that GLOEMP characterizes image information across different directions, it contains very abundant information. The global-level rotation compensation method is proposed, which shifts the principal orientation of the HOG to the first position, thus allowing GLOEMP to be robust to rotations. In addition, gradient magnitudes are used as weights to add to the histogram, making GLOEMP robust to lighting variances as well, and it also possesses a strong ability to express edge information. The experimental results obtained from the representative databases demonstrate that the proposed GLOEMP framework is capable of achieving significant improvement, in some cases reaching classification accuracy of 10% higher than over the traditional rotation invariant LBP method. <\/jats:p>","DOI":"10.1142\/s0218001417500070","type":"journal-article","created":{"date-parts":[[2016,7,22]],"date-time":"2016-07-22T04:45:46Z","timestamp":1469162746000},"page":"1750007","source":"Crossref","is-referenced-by-count":1,"title":["Global and Local Oriented Edge Magnitude Patterns for Texture Classification"],"prefix":"10.1142","volume":"31","author":[{"given":"Jun","family":"Dong","sequence":"first","affiliation":[{"name":"Institute of Intelligent Machines, Hefei Institute of Physical Science Chinese Academy of Sciences, Hefei 230031, P. R. China"},{"name":"School of Information Science and Engineering, Southeast University, Nanjing 210096, P. R. China"},{"name":"Wuxi Zhongke Intelligent Agricultural Development Co. Ltd., Wuxi 21000, P. R. China"},{"name":"Jiangsu R&amp;D Center for Internet of Things, Wuxi 21000, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xue","family":"Yuan","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Beijing Jiaotong University, No. 3 Shang Yuan Cun, Hai Dian District, Beijing, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fanlun","family":"Xiong","sequence":"additional","affiliation":[{"name":"Institute of Intelligent Machines, Hefei Institute of Physical Science Chinese Academy of Sciences, Hefei 230031, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2017,2]]},"reference":[{"key":"S0218001417500070BIB004","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2009.08.017"},{"key":"S0218001417500070BIB005","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2044957"},{"key":"S0218001417500070BIB007","doi-asserted-by":"publisher","DOI":"10.1109\/83.743859"},{"key":"S0218001417500070BIB010","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2042100"},{"key":"S0218001417500070BIB011","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2009.2015682"},{"key":"S0218001417500070BIB013","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2012.2188809"},{"key":"S0218001417500070BIB014","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2002.1017623"},{"key":"S0218001417500070BIB015","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2004.01.011"},{"key":"S0218001417500070BIB016","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2011.2166974"},{"key":"S0218001417500070BIB020","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2006.884956"},{"issue":"10","key":"S0218001417500070BIB021","first-page":"2617","volume":"16","author":"Zou J.","year":"2007","journal-title":"Neurocomputing"},{"key":"S0218001417500070BIB022","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.05.016"},{"key":"S0218001417500070BIB023","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2012.10.017"},{"key":"S0218001417500070BIB024","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2507408"},{"key":"S0218001417500070BIB025","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2015.08.025"},{"key":"S0218001417500070BIB026","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2013.2258010"}],"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218001417500070","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T08:39:58Z","timestamp":1565080798000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218001417500070"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,2]]},"references-count":16,"journal-issue":{"issue":"03","published-online":{"date-parts":[[2017,2]]},"published-print":{"date-parts":[[2017,3]]}},"alternative-id":["10.1142\/S0218001417500070"],"URL":"https:\/\/doi.org\/10.1142\/s0218001417500070","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"type":"print","value":"0218-0014"},{"type":"electronic","value":"1793-6381"}],"subject":[],"published":{"date-parts":[[2017,2]]}}}