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A sparse kernel representation method for image classification | IEEE Conference Publication | IEEE Xplore
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A sparse kernel representation method for image classification


Abstract:

In this paper, we propose a sparse kernel representation classification algorithm (SKRC) for images classification and recognition. The training dictionary is composed by...Show More

Abstract:

In this paper, we propose a sparse kernel representation classification algorithm (SKRC) for images classification and recognition. The training dictionary is composed by labeled samples directly, and both training dictionary and testing sample are mapped into feature space from original sample space by the sparse kernel which employs the “center” samples matrix constructed by a method similar to k-means clustering. Then in the feature space, the basic sparse representation based classification method is employed. We test our proposed algorithm on some different public database, and the results show that our proposed method can achieve higher classification accuracy without much time consumed.
Date of Conference: 10-15 June 2012
Date Added to IEEE Xplore: 30 July 2012
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ISSN Information:

Conference Location: Brisbane, QLD

References

References is not available for this document.