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