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Math. Comput. Appl. 2017, 22(1), 8; doi:10.3390/mca22010008

A Sparse Representation Algorithm for Effective Photograph Retrieval

Department of Computer Science and Technology, Huaqiao University, Fujian 361021, China
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Authors to whom correspondence should be addressed.
Academic Editor: Fazal M. Mahomed
Received: 17 July 2016 / Revised: 5 December 2016 / Accepted: 11 January 2017 / Published: 18 January 2017
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Abstract

Searching through information based on a photograph, which may contain graphics and images, has become a popular trend, such as in electronic books, journals, and products. Although many context-based methods have been proposed to retrieve images, most work focuses on selecting appropriate features for different objects. In the present study, we apply sparse representation to simultaneously retrieve image and graphics from a photograph. The sparse vector can be regarded as the similarity between the query photograph and dataset. The image with the largest entry (or several largest entries) can be assigned as the retrieved result. In the sparse representation framework, the common image features are used. Experimental results demonstrate that if the similarity vector in photograph retrieval is sparse, feature extraction is no longer critical. Compared with similar works in photograph retrieval, the proposed method has better retrieval accuracy. View Full-Text
Keywords: photograph retrieval; sparse representation; similarity; sparse vector; feature extraction photograph retrieval; sparse representation; similarity; sparse vector; feature extraction
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MDPI and ACS Style

Zhang, H.-B.; Lei, Q.; Zhong, B.-N.; Du, J.-X.; Chen, D.-S. A Sparse Representation Algorithm for Effective Photograph Retrieval. Math. Comput. Appl. 2017, 22, 8.

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