Background Segmentation in Color Image Using Self-Organizing Feature Selection 


Vol. 15,  No. 5, pp. 407-412, Oct.  2008
10.3745/KIPSTB.2008.15.5.407


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  Abstract

Color segmentation is one of the most challenging problems in image processing especially in case of handling the images with cluttered background. Great amount of color segmentation methods have been developed and applied to real problems. In this paper, we suggest a new methodology. Our approach is focused on background extraction, as a complimentary operation to standard foreground object segmentation, using self-organizing feature selective property of unsupervised self-learning paradigm based on the competitive algorithm. The results of our studies show that background segmentation can be achievable in efficient manner.

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[IEEE Style]

H. K. Shin, "Background Segmentation in Color Image Using Self-Organizing Feature Selection," The KIPS Transactions:PartB , vol. 15, no. 5, pp. 407-412, 2008. DOI: 10.3745/KIPSTB.2008.15.5.407.

[ACM Style]

Hyun Kyung Shin. 2008. Background Segmentation in Color Image Using Self-Organizing Feature Selection. The KIPS Transactions:PartB , 15, 5, (2008), 407-412. DOI: 10.3745/KIPSTB.2008.15.5.407.

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