DocumentCode
419617
Title
Binarization of color images from an adaptation of possibilistic c-means algorithm
Author
Tabbone, Salvatore ; Wendling, Laurent
Author_Institution
LORIA-INRIA, Nancy II Univ., Vandoeuvre-les-Nancy, France
Volume
1
fYear
2004
fDate
23-26 Aug. 2004
Firstpage
704
Abstract
A color image binarization is presented in this paper. The iterative possibilistic c-means algorithm is adapted by adding a fuzzy entropy criterion to split the membership function into two clusters (background and object). Such an improvement allows to perform a threshold free color binarization. Experimental results show the promising aspect of our approach.
Keywords
fuzzy set theory; image colour analysis; image segmentation; iterative methods; pattern clustering; color image binarization; fuzzy entropy methods; fuzzy membership function; image segmentation; iterative algorithm; pattern clustering; possibilistic c-means algorithm; Character generation; Clustering algorithms; Color; Content based retrieval; Entropy; Image databases; Image retrieval; Image segmentation; Iterative algorithms; Pixel;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
ISSN
1051-4651
Print_ISBN
0-7695-2128-2
Type
conf
DOI
10.1109/ICPR.2004.1334277
Filename
1334277
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