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Given the variety of possible image characteristics that may have to be processed, the proposed model can adaptively adjust the weighting to drive curve evolution trends and states. In this way, the intensity information of weak boundaries and complex backgrounds can be extracted more precisely, thus enabling the model to produce better results for low\u2010contrast images and complex structures. In addition, a Gaussian filtering process has been added to the model to smooth and standardize the level set function, and a parameter has been introduced to speed up the curve evolution. A penalty term is also used to eliminate the need for complex re\u2010initialization procedures. Experimental results for various kinds of images efficiently demonstrate the good performance of the proposed model in terms of both speed and accuracy. \u00a9 2016\nWiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 179\u2013187, 2016<\/jats:p>","DOI":"10.1002\/ima.22173","type":"journal-article","created":{"date-parts":[[2016,8,16]],"date-time":"2016-08-16T15:20:19Z","timestamp":1471360819000},"page":"179-187","source":"Crossref","is-referenced-by-count":3,"title":["Image segmentation model based on adaptive adjustment of global and local information"],"prefix":"10.1002","volume":"26","author":[{"given":"Xianghai","family":"Wang","sequence":"first","affiliation":[{"name":"School of Computer and Information Technology Liaoning Normal University Dalian City Liaoning Province 116029 China"},{"name":"School of Mathematics Liaoning Normal University Dalian City Liaoning Province 116029 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruoxi","family":"Song","sequence":"additional","affiliation":[{"name":"School of Computer and Information Technology Liaoning Normal University Dalian City Liaoning Province 116029 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chong","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mathematics Liaoning Normal University Dalian City Liaoning Province 116029 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer and Information Technology Liaoning Normal University Dalian City Liaoning Province 116029 China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingling","family":"Fang","sequence":"additional","affiliation":[{"name":"School of Computer and Information Technology Liaoning Normal University Dalian City Liaoning Province 116029 China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2016,8,16]]},"reference":[{"key":"e_1_2_5_2_1","first-page":"1","article-title":"active contours and image segmentation: The current state of the art","volume":"12","author":"Baswaraj D.","year":"2012","journal-title":"Global J Comput Sci Technol Graph Vis"},{"key":"e_1_2_5_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/83.902291"},{"key":"e_1_2_5_4_1","first-page":"681","article-title":"on the generalized Euler\u2010Lagrange equation","volume":"213","author":"Chen J.W.","year":"1997","journal-title":"J Math Anal Appl"},{"key":"e_1_2_5_5_1","doi-asserted-by":"publisher","DOI":"10.1002\/ima.22010"},{"key":"e_1_2_5_6_1","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/s005260000065","article-title":"optimal Lipschitz extensions and the infinity Laplacian","volume":"13","author":"Grandall M.G.","year":"2001","journal-title":"Calc Var Partial Diff Equ"},{"key":"e_1_2_5_7_1","unstructured":"M.Li Image segmentation technology research based on partial differential equation Master Dissertation of Liaoning Normal University Dalian China 2013."},{"key":"e_1_2_5_8_1","unstructured":"C.Li C.Xu C.Gui andM.D.Fox Level set evolution without re\u2010initialization: A new variational formulation IEEE Conf Comput Vis Pattern Recogn Los Alamitos 2005 pp.430\u2013436."},{"key":"e_1_2_5_9_1","doi-asserted-by":"crossref","unstructured":"C.Li C.Kao J.C.Gore andZ.Ding implicit active contours driven by local binary fitting energy Proc IEEE Conf Comput Vis Pattern Recogn Washington DC 2007 pp.17\u201322.","DOI":"10.1109\/CVPR.2007.383014"},{"key":"e_1_2_5_10_1","doi-asserted-by":"crossref","unstructured":"C.Li C.Kao andC.Gore Minimization of region scalable fitting energy for image segmentation. 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