DocumentCode :
3063787
Title :
Histogram based fuzzy C-mean algorithm for image segmentation
Author :
Qing, Ye Xiu ; Hua, Huang Zhen ; Qiang, Xiao
Author_Institution :
Zhejiang Univ., Hangzhou, China
fYear :
1992
fDate :
30 Aug-3 Sep 1992
Firstpage :
704
Lastpage :
707
Abstract :
Since a real image is usually very complex, there must be some uncertainties and errors in image segmentation. The fuzzy C-mean (FCM) algorithm can overcome this problem, but the cost will be a large amount of computation time. The authors present an improved FCM algorithm which uses a histogram, instead of the gray function, to find centers of the gray level. Theoretical analysis and experiment results show that it can reduce the computing time significantly
Keywords :
fuzzy set theory; image recognition; image segmentation; fuzzy C-mean algorithm; gray level; histogram; image recognition; image segmentation; Clustering algorithms; Fuzzy sets; Histograms; Image processing; Image segmentation; Iterative algorithms; Layout; Pattern recognition; Pixel; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1992. Vol.III. Conference C: Image, Speech and Signal Analysis, Proceedings., 11th IAPR International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-8186-2920-7
Type :
conf
DOI :
10.1109/ICPR.1992.202084
Filename :
202084
Link To Document :
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