Fast Evolution of Curve Based On Chan-Vese Model for Specific Images

-In image processing, segmentation is an important intermediate step for object recognition. It is a fundamental task in image analysis responsible for partitioning an image into multiple sub-regions based on a desired feature. One such technique is through Curve Evolution and one of the applications of Geometric Curve Evolution is Active Contours. In the research work being reported in this paper an attempt has been made to enhance Chan-Vese [1] Algorithm faster by taking different planes (red, green and blue) of an image. The plane in which the contour evolves fastest gets automatically selected and rest of the algorithm will work on that particular plane. Experimental results are presented on various domains like biomedical images, artificial images and painted images. Also, the contour evolves differently in different planes. Key Termsactive contour, objects, object recognition, segmentation, standard deviation