DocumentCode :
1591693
Title :
Color image edge detection using cluster analysis
Author :
Tao, Hai ; Huang, Thomas S.
Author_Institution :
Beckman Inst., Illinois Univ., Urbana, IL, USA
Volume :
1
fYear :
1997
Firstpage :
834
Abstract :
A color image edge detection algorithm is proposed based on the idea that use global color information to guide local gradient computation. The major chromatic components of an image are first extracted through cluster analysis. According to these color clusters, a set of linear chromatic transforms are generated. An appropriate chromatic transform is chosen for each pixel to maximize the gradient magnitude. In this way, edges are treated as transitions from one cluster to another. The algorithm is implemented and experimental results for real color images are included
Keywords :
feature extraction; image colour analysis; transforms; chromatic components; cluster analysis; color clusters; color image edge detection algorithm; experimental results; feature extraction; global color information; gradient magnitude; linear chromatic transforms; local gradient computation; pixel; real color images; Clustering algorithms; Colored noise; Humans; Image analysis; Image color analysis; Image edge detection; Machine vision; Pixel; Statistical distributions; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1997. Proceedings., International Conference on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
0-8186-8183-7
Type :
conf
DOI :
10.1109/ICIP.1997.648093
Filename :
648093
Link To Document :
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