{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T14:09:07Z","timestamp":1753884547088,"version":"3.41.2"},"reference-count":34,"publisher":"World Scientific Pub Co Pte Ltd","issue":"07","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J CIRCUIT SYST COMP"],"published-print":{"date-parts":[[2022,5,15]]},"abstract":"<jats:p> Image segmentation is an important processing technology, which is the basis of image recognition and has been widely used in many fields. In this paper, we propose a method, termed coarse-to-fine strategy-based image segmentation (CSIS), for color image segmentation. The basic idea is to segment an image by three phases: (1) the original image is first segmented into several distinct regions by using the mean shift method; (2) the segmented regions are converted to a weighted region adjacency graph (RAG), and a new graph cut method, called multi-cut algorithm, is proposed to partition the RAG into multiple regions; (3) a one-step Chan\u2013Vese algorithm is applied to smooth the boundaries of the segmented objectives. In each of the last two phases, a method is applied to refine the result obtained in the previous phase. By carefully balancing the efforts used in each phase, CSIS could segment color images both efficiently and effectively. These advantages are demonstrated by applying the proposed method to a variety of test instances, and the statistical results also show that it is comparable with some state-of-the-art methods. <\/jats:p>","DOI":"10.1142\/s0218126622501237","type":"journal-article","created":{"date-parts":[[2022,2,4]],"date-time":"2022-02-04T04:53:40Z","timestamp":1643950420000},"source":"Crossref","is-referenced-by-count":1,"title":["Color Image Segmentation by Utilizing Coarse-to-Fine Strategy"],"prefix":"10.1142","volume":"31","author":[{"given":"Yingxia","family":"Chen","sequence":"first","affiliation":[{"name":"School of Computer Science, Yangtze University, Jingzhou 434023, Hubei, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Computer Science, Yangtze University, Jingzhou 434023, Hubei, P. R. 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