Level Set Based Image Segmentation Using Momentum and Resilient Propagation
Dhanraj Katta1, G. Raghotham Reddy2, R. Srikanth3
1Dhanraj Katta, M.Tech MIETE Electronic & Communication Engineering, KITS, Warangal, (A.P), India.
2G. Raghotham Reddy, M.Tech MIEEE, MIETE, MISTE Assoc. Professor & Head Dept, of ECE, KITS Warangal, (A.P), India.
3Rangu Srikanth, M.Tech MIEEE, MIETE, Assistant Professor Dept, of ECE, KITS Warangal, (A.P), India.
Manuscript received on September 25, 2013. | Revised Manuscript received on October 12, 2013. | Manuscript published on October 30, 2013. | PP: 73-79 | Volume-3, Issue-1, October 2013. | Retrieval Number: A2154103113/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Active contour, Gradient methods, Image segmentation, Level set method, Optimization.