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Image segmentation Based on Chan-Vese Active Contours using Finite Difference Scheme


Mr. Rajesh A. Jadav , S.V.M. Institute of Technology, Bharuch; Dr. Shailesh S. Patel, S.V.M. Institute of Technology, Bharuch; Dr. Dilip C. Joshi, Veer Narmad South Gujarat University, Surat, Gujarat. India.


Image Segmentation, Chan-Vese model, Active contours, Level set method, Finite difference method, Partial Differential Equation.


There are a lot of image segmentation techniques that try to differentiate between backgrounds and object pixels but many of them fail to discriminate between different objects that are close to each other, e.g. low contrast between foreground and background regions increase the difficulty for segmenting images. So we introduced the Chan-Vese active contours model for image segmentation to detect the objects in given image, which is built based on techniques of curve evolution and level set method. The Chan-Vese model is a special case of Mumford-Shah functional for segmentation and level sets. It differs from other active contour models in that it is not edge dependent, therefore it is more capable of detecting objects whose boundaries may not be defined by a gradient. Finally, we developed code in Matlab 7.8 for solving resulting Partial differential equation numerically by the finite differences schemes on pixel-by-pixel domain.

Other Details

Paper ID: IJSRDV1I6013
Published in: Volume : 1, Issue : 6
Publication Date: 01/09/2013
Page(s): 1322-1326

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