DocumentCode
2377608
Title
Segmentation of color image by ϕβ criterion fuzzy theory
Author
El Matouat, Abdelaziz ; Hamzaoui, Hassania ; Martin, Patrick
Author_Institution
CERENE, Le Havre Univ.
fYear
2006
fDate
6-10 Nov. 2006
Firstpage
3419
Lastpage
3423
Abstract
In this paper, we propose to use the information criterion ϕβ to identify the optimal number of clusters in the segmentation of a color image. The performance of this criterion is verified on the image test "House", "Monarch", "Lenna" and "Peppers", and compared with the selection obtained by the Chen and Lu fuzzy segmentation method. We verify that the new proposed method is efficient with respect to Chen\´s algorithm. We finally propose an appropriate choice for the radius in order to have an optimal segmentation of the image
Keywords
fuzzy set theory; image colour analysis; image segmentation; ϕβ criterion; color image segmentation; fuzzy theory; Clustering algorithms; Colored noise; Fuzzy sets; Histograms; Image color analysis; Image segmentation; Maximum likelihood detection; Maximum likelihood estimation; Pattern recognition; Pixel; ϕβ criterion; Fuzzy clustering algorithm; Fuzzy sets; Histogram; Information criteria;
fLanguage
English
Publisher
ieee
Conference_Titel
IEEE Industrial Electronics, IECON 2006 - 32nd Annual Conference on
Conference_Location
Paris
ISSN
1553-572X
Print_ISBN
1-4244-0390-1
Type
conf
DOI
10.1109/IECON.2006.347677
Filename
4153683
Link To Document