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ASME Press Select Proceedings

International Conference on Electronics, Information and Communication Engineering (EICE 2012)

By
Garry Lee
Garry Lee
Information Engineering Research Institute
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ISBN:
9780791859971
No. of Pages:
1008
Publisher:
ASME Press
Publication date:
2012

Unsupervised image segmentation (UIS) is a very challenging problem in computer vision and artificial intelligence. In general, the UIS can be viewed as a clustering problem, which aims to partition the image into K sets of regions that have coherent color and texture features. Clearly, the UIS results depend on the employed clustering methods. Inspired by the recent rapid progress of l1-norm minimization techniques and the great success of l1-norm minimization based sparse representation (SR), in this paper we propose a K-sparse clustering algorithm to segment the image into K partitions. The given...

Abstract
Keywords
Introduction
Sparse Representation (SR)
Image Segmentation by K-Sparse Clustering
Problem Formulation
Computing the K-Sparse Clustering Centers
Segmentation via K-Sparse Clustering
Experimental Results
Conclusion
Acknowledgments
References
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