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2006
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Efficient Bottom-Up Image Segmentation Using Region Competition and the Mumford-Shah Model for Color and Textured Images

8 years 10 months ago
Efficient Bottom-Up Image Segmentation Using Region Competition and the Mumford-Shah Model for Color and Textured Images
Curve evolution implementations [3][23] [25] of the Mumford-Shah functional [16] are of broad interest in image segmentation. These implementations, however, have initialization problems [6] [25]. A mathematical analysis of the initialization problem for the Chan-Vese implementation [3] [25] is provided in this paper. The initialization problem is a result of the non-convexity of the MumfordShah functional and the top-down hierarchy of the model's use of global region information in the image. Based on the analysis, efficient implementation methods are proposed for the Chan-Vese models [3] [25]. The proposed methods do not have to solve PDEs and thus work fast. The advantages of level set methods, such as automatic handling of topological changes, are preserved. These methods work well for images without strong noise. Initialization problems, however, still exist. A bottom-up image segmentation method is proposed that alleviates the initialization problem, based on region competi...
Yongsheng Pan, J. Douglas Birdwell, Seddik M. Djou
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2006
Where ISM
Authors Yongsheng Pan, J. Douglas Birdwell, Seddik M. Djouadi
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