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JPEG compressed image retrieval via statistical features

delete2003-04-01
delete62
PRE
AI
G
Guocan Feng
J
Jianmin Jiang
DOI：10.1016/S0031-3203(02)00114-0delete
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Abstract

Abstract

En 中文
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. Crown Copyright (C) 2002 Published by Elsevier Science Ltd on behalf of Pattern Recognition Society. All rights reserved.
Keywords:
DCT
statistical feature extraction
compressed image retrieval
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Journal

Pattern Recognition cover
Pattern Recognition
IF:
7.6
Papers:
1.3W
Citations:
4.5W

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