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Rotation invariant simultaneous clustering and dictionary learning
Y.-C. Chen, , V.M. Patel, P.J. Phillips, R. Chellappa
Published in
2012
Pages: 1053 - 1056
Abstract
In this paper, we present an approach that simultaneously clusters database members and learns dictionaries from the clusters. The method learns dictionaries in the Radon transform domain, while clustering in the image domain. Themain feature of the proposed approach is that it provides rotation invariant clustering which is useful in Content Based Image Retrieval (CBIR). We demonstrate through experimental results that the proposed rotation invariant clustering provides better retrieval performance than the standard Gabor-based method that has similar objectives. © 2012 IEEE.
About the journal
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN15206149