JPEG compressed image retrieval via statistical features |
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Authors: | Guocan FengAuthor Vitae Jianmin JiangAuthor Vitae |
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Affiliation: | a Department of Electronic Imaging and Media Communications, School of Informatics, University of Bradford, Bradford, BD7 1DP, UK b Zhongshan University, Guangzhou, China |
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Abstract: | To improve efficiency of compressed image retrieval, we propose a novel statistical feature extraction algorithm in this paper to characterize the image content directly in its compressed domain. The statistical feature extracted is mainly through computing a set of moments directly from DCT coefficients without involving full decompression or inverse DCT. Following the algorithm design, a content-based image retrieval system is implemented especially targeting retrieving joint picture expert group compressed images. Theoretical analysis and experimental results support that the system is robust to translation, rotation and scale transform with minor disturbance, and the system achieves good performances in terms of retrieval efficiency and effectiveness. |
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Keywords: | DCT Statistical feature extraction Compressed image retrieval |
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