In-plane rotation and scale invariant clustering using dictionaries

Chen, Y C and Sastry, C S and Patel, V M and Phillips, P J and Chellappa, R (2013) In-plane rotation and scale invariant clustering using dictionaries. IEEE Transactions on Image Processing, 22 (6). pp. 2166-2180. ISSN 1057-7149

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In this paper, we present an approach that simultaneously clusters images and learns dictionaries from the clusters. The method learns dictionaries and clusters images in the radon transform domain. The main feature of the proposed approach is that it provides both in-plane rotation and scale invariant clustering, which is useful in numerous applications, including content-based image retrieval (CBIR). We demonstrate the effectiveness of our rotation and scale invariant clustering method on a series of CBIR experiments. Experiments are performed on the Smithsonian isolated leaf, Kimia shape, and Brodatz texture datasets. Our method provides both good retrieval performance and greater robustness compared to standard Gabor-based and three state-of-the-art shape-based methods that have similar objectives

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IITH Creators:
IITH CreatorsORCiD
Item Type: Article
Uncontrolled Keywords: Clustering; content-based image retrieval (CBIR); dictionary learning; radon transform; rotation invariance; scale invariance
Subjects: ?? sub3.8 ??
Divisions: Department of Mathematics
Depositing User: Team Library
Date Deposited: 01 Dec 2014 09:03
Last Modified: 01 Dec 2014 09:03
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