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An Improved Suppressed FCM Algorithm for Image Segmentation

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Abstract:

Fuzzy C-Means clustering(FCM) algorithm plays an important role in image segmentation, but it is sensitive to noise because of not taking into account the spatial information. Addressing this problem, this paper presents an improved suppressed FCM algorithm based on the pixels and the spatial neighborhood information of the image. The algorithm combines the two-dimentional histogram and suppressed FCM algorithm together. First, construct a two-dimentional histogram instead of one-dimentional histogram, which can better distinguish the distribution of the object and background for noisy images. Then determine the initial clustering based on two-dimensional histogram. Last, provide a new way to determine the suppressed factor and use the improved FCM algorithm to realize the image segmentation. Experimental results show that the improved algorithm is effective to improve the clustering speed, and can achieve better segmentation results.

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Info:

Periodical:

Advanced Materials Research (Volumes 712-715)

Pages:

2349-2353

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.712-715.2349

Citation:

Cite this paper

Online since:

June 2013

Authors:

Hong Lan, Shao Bin Jin

Keywords:

Fuzzy C-Means Clustering, Image Segmentation, Neighborhood Information, Suppressed FCM Algorithm

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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