Level Set Based Image Segmentation Using Momentum and Resilient Propagation
Dhanraj Katta, Srikanth Ryali · 2013
In this paper image segmentation problems are solved by using the level set methods. Level Set Methods are involves to optimize the contour space and cost functional is minimized. Gradient descent methods are often used to solve this optimization problem since they are very easy to implement and applicable to general no convex functional. They are, however, sensitive to local minima and often display slow convergence. Traditionally, cost functional has been modified to avoid these problems. In this paper, I propose level set based image segmentation using momentum and resilient propagation. The proposed methods are very simple modifications of the basic method, and are directly compatible with any type of level set implementation. This approach consists of using the algorithmic core for processing images to detect parameter sensitivity is investigated. Index Terms—Active contour, gradient methods, image segmentation, level set method, optimization.