Fusion of Fuzzy Set and FCM for Image Segmentation

Chao Quan Zhang; Liang Chen; Shao Jing Zhou

doi:10.4028/www.scientific.net/AMM.182-183.723

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 182-183Fusion of Fuzzy Set and FCM for Image Segmentation

Fusion of Fuzzy Set and FCM for Image Segmentation

Abstract:

Image segmentation with the traditional Fuzzy C-means (FCM) algorithm only uses each pixel’s gray value, when the image is corrupted by noises, the accuracy of segmentation will be greatly reduced. So, this paper proposed an image segmentation method which based on rough sets theory and fuzzy c-mean clustering. The test result shows that the method has a good segmentation performance.

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Periodical:

Applied Mechanics and Materials (Volumes 182-183)

Pages:

723-728

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.182-183.723

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Online since:

June 2012

Authors:

Chao Quan Zhang, Liang Chen, Shao Jing Zhou

Keywords:

Cluster, Fuzzy C-Means (FCM), Image Segmentation, Rough Set (RS)

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