Watershed Image Segmentation Based on PSO and FCM

Gui Shui Yu; Ke Li

doi:10.4028/www.scientific.net/AMR.1070-1072.2041

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1070-1072Watershed Image Segmentation Based on PSO and FCM

Watershed Image Segmentation Based on PSO and FCM

Abstract:

A watershed segmentation algorithm based on fuzzy C-means clustering () was proposed in this paper , which can solve the problem of over-segmentation in sonar image processing. Firstly, the original image was transformed to be gray image and then segmented by watershed algorithm. Secondly, the improved particle swarm optimization () was used to find the accurate original clustering centers of . Finally, with the accurate centers and the improved target function, the small regions of the initial segmented image was clustered by . The iterating number was controlled to increase segmenting speed. Additionally, the high sonar image segmentation efficiency is testified in the experiment and the problem of over-segmentation is restricted.

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Periodical:

Advanced Materials Research (Volumes 1070-1072)

Pages:

2041-2044

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1070-1072.2041

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Online since:

December 2014

Authors:

Gui Shui Yu, Ke Li*

Keywords:

Fuzzy Clustering, Image Segmentation, Particle Swarm Optimization (PSO), Watershed

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