Image segmentation using probabilistic fuzzy c-means clustering

A new approach for gray-level image segmentation is presented using a probabilistic fuzzy c-means clustering algorithm. This approach combines the spatial probabilistic information and the fuzzy membership function in the clustering process. The proposed probabilistic fuzzy c-means method can deal e...

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Bibliographic Details
Published in2001 International Conference on Image Processing Vol. 1; pp. 722 - 725 vol.1
Main Author Pham, T.D.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2001
Subjects
Clustering algorithms
Design automation
Equations
Image edge detection
Image segmentation
Iterative algorithms
Merging
Pixel
Virtual colonoscopy
Working environment noise
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ISBN0780367251
9780780367258
DOI10.1109/ICIP.2001.959147

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Summary:A new approach for gray-level image segmentation is presented using a probabilistic fuzzy c-means clustering algorithm. This approach combines the spatial probabilistic information and the fuzzy membership function in the clustering process. The proposed probabilistic fuzzy c-means method can deal effectively with image segmentation in a noisy environment.
ISBN:0780367251
9780780367258
DOI:10.1109/ICIP.2001.959147