International Conference on Advanced Computing, Communication and Networks - CCN 2011
Author(s) : G. RAMESH, G.NARSIMHULU
Image segmentation is one of the most important steps in image analysis and has been a key problem in computer vision. The main aim of this process is to separate an image to several regions or parts which correlate strongly the interested objects. Snakes, or active contours, have been widely used to locate boundaries of image segmentation and computer vision. Problem associated with the existence of the local minima in the active contour energy function makes snakes have poor convergence in segmentation process; therefore, the poor convergence has limited applications. In this work, a fast minimization of snake model is used for an MRI knee image segmentation. This method provides a satisfied result. As a result, it is a good candidate for MRI image segmentation approach. In other words an improper initial contour can give inaccurate result. The problem with the initial contour relates to the nonconvexity of the energy function, EGAC , to be minimized and then the existence of the local minimum.