DocumentCode :
1852177
Title :
Rough segmentation of natural color images using fuzzy-based hierarchical algorithm
Author :
Maeda, Junji ; Saga, Sato ; Suzuki, Yukinori
Author_Institution :
Dept. of Comput. Sci. & Syst. Eng., Muroran Inst. of Technol., Japan
Volume :
1
fYear :
2004
fDate :
25-28 July 2004
Abstract :
This paper proposes rough segmentation of natural color images using fuzzy-based hierarchical algorithm. Statistical geometrical features (SGF) are adopted as texture features and L*a*b* color space is used to represent a color feature. Fuzzy homogeneity decision makes a fusion of texture features and color features. Proposed hierarchical segmentation method based on the fuzzy homogeneity decision is performed in four stages: hierarchical splitting, local agglomerative merging, global agglomerative merging and pixelwise classification. Experiments on segmentation of natural color images are presented to verify the effectiveness of the proposed method in obtaining rough segmentation.
Keywords :
decision theory; feature extraction; fuzzy set theory; image classification; image colour analysis; image segmentation; image texture; rough set theory; statistical analysis; L*a*b* color space; color features; fuzzy based hierarchical algorithm; fuzzy homogeneity decision; hierarchical segmentation method; hierarchical splitting technique; local agglomerative merging technique; natural color images; pixelwise classification; rough segmentation; statistical geometrical features; texture features; Color; Computer science; Gabor filters; Graph theory; Image recognition; Image segmentation; Merging; Paper technology; Space technology; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 2004. MWSCAS '04. The 2004 47th Midwest Symposium on
Print_ISBN :
0-7803-8346-X
Type :
conf
DOI :
10.1109/MWSCAS.2004.1353936
Filename :
1353936
Link To Document :
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