DocumentCode
2382692
Title
A modified FCM with optimal Peano scans for image segmentation
Author
Hafiane, A. ; Zavidovique, B. ; Chaudhuri, S.
Author_Institution
Inst. d´´Electronique Fondamentale, Paris Univ., Orsay, France
Volume
3
fYear
2005
fDate
11-14 Sept. 2005
Abstract
This paper describes a new method for fuzzy segmentation based on spatial constraints. Taking into account the neighborhood influence two techniques are used. First a new feature is derived from Peano scans to represent a spatial relationship among neighbors. Second we incorporate a regularization term to fuzzy C-means algorithm (FCM). The algorithm is tested on both synthetic and multispectral images. Experimental results are presented and discussed. They show the effectiveness of the method.
Keywords
fuzzy set theory; image segmentation; fuzzy C-means algorithm; fuzzy segmentation; image segmentation; multispectral images; optimal Peano scans; spatial constraints; synthetic images; Clustering algorithms; Clustering methods; Computer vision; Image analysis; Image segmentation; Image texture analysis; Multispectral imaging; Pattern recognition; Pixel; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 2005. ICIP 2005. IEEE International Conference on
Print_ISBN
0-7803-9134-9
Type
conf
DOI
10.1109/ICIP.2005.1530523
Filename
1530523
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