Advanced FCM Algorithm for Segmentation
R. Saranya Pon Selvi3, C.Akila2
1R. Saranya Pon Selvi, Computer Science and Engineering, Regional Centre Anna University, (Tamil Nadu), India.
2C. Akila, Computer Science and Engineering, Regional Centre, Anna University, (Tamil Nadu), India.
Manuscript received on January 25, 2014. | Revised Manuscript received on February 13, 2014. | Manuscript published on February 28, 2014. | PP: 123-128 | Volume-3, Issue-3, February 2014. | Retrieval Number: C2603023314/2013©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: An advanced FCM Algorithm is introduced to segment the image which is affected by noise, outliers or any other artifacts. In order to segment those images this algorithm is introduced. By using this algorithm both noise can be removed and the segmentation can be made efficiently. The trade-off weighted fuzzy factor and kernel distance measure are both used in the introduced algorithm and both are parameters free. By using the fuzzy factor, the damping extent of the neighbouring pixels can be estimated accurately. The experimental results also show that the algorithm is effective and efficient and it is independent of the type of the noises.
Keywords: Fuzzy clustering, Gray-level constraint, Image segmentation, kernel metric, Spatial constraint.