A Sparse Representation Algorithm for Effective Photograph Retrieval
AbstractSearching 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
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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.
Zhang H-B, Lei Q, Zhong B-N, Du J-X, Chen D-S. A Sparse Representation Algorithm for Effective Photograph Retrieval. Mathematical and Computational Applications. 2017; 22(1):8.Chicago/Turabian Style
Zhang, Hong-Bo; Lei, Qing; Zhong, Bi-Neng; Du, Ji-Xiang; Chen, Duan-Sheng. 2017. "A Sparse Representation Algorithm for Effective Photograph Retrieval." Math. Comput. Appl. 22, no. 1: 8.
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