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A sparse kernel representation method for image classification

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3 Author(s)
Shuyuan Yang ; Dept. of Electron. Eng., Key Lab. of Intell. Perception & Image Understanding, Xidian Univ., Xi''an, China ; Yue Han ; XiangRong Zhang

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.

Published in:

Neural Networks (IJCNN), The 2012 International Joint Conference on

Date of Conference:

10-15 June 2012

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