DocumentCode
397082
Title
Color image segmentation using connected regions
Author
Wesolkowski, Slawo ; Fieguth, Paul
Author_Institution
Dept. of Syst. Design, Waterloo Univ., Ont., Canada
Volume
2
fYear
2003
fDate
4-7 May 2003
Firstpage
1203
Abstract
A color image segmentation algorithm based on region growing is presented. Each region is characterized using two parameters: within region color contrast and between region color contrast. The first parameter is the distance between the two most distant pixels in terms of color. The second parameter is the distance between the candidate pixel and its nearest neighbor in the region. The color similarity measure used is the vector angle, which is invariant to shading. Highlight invariance is accomplished by using a highlight removal transformation, which removes the average pixel intensity from each RGB coordinate. The first calculation is very computationally intensive. To reduce this computational burden, the algorithm keeps track of which pixels already in the region are furthest spatially from the pixel being considered. The assumption would be that the pixels the furthest away would be the ones most different from the pixel being considered. We will present results on artificial and real images to illustrate the effectiveness of the method.
Keywords
image colour analysis; image segmentation; realistic images; RGB coordinate; color image segmentation; color similarity measure; connected region; highlight invariance; highlight removal transformation; pixel intensity; real image; shading invariance; vector angle; Clustering algorithms; Euclidean distance; Humans; Image color analysis; Image segmentation; Lighting; Nearest neighbor searches; Optical reflection; Prototypes; Random access memory;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Computer Engineering, 2003. IEEE CCECE 2003. Canadian Conference on
ISSN
0840-7789
Print_ISBN
0-7803-7781-8
Type
conf
DOI
10.1109/CCECE.2003.1226114
Filename
1226114
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