Retrieving digital images from a JPEG compressed image database

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摘要

In this paper, we propose a new method of feature extraction in order to improve the efficiency of retrieving Joint Photographic Experts Group (JPEG) compressed images. Our feature extraction can be done directly to JPEG compressed images. We extract two features, DC feature and AC feature, from a JPEG compressed image. Then we measure the distances between the query image and the images in a database in terms of these two features. Our image retrieval system will give each retrieved image a rank to define its similarity to the query image. Furthermore, instead of fully decompressing JPEG images, our system only needs to do partial entropy decoding. Therefore, our proposed scheme can accelerate the work of retrieving images. According to our experimental results, our system is not only highly efficient but is also capable of performing satisfactorily.

论文关键词:Quadtree,Image database,Image retrieval,Joint photographic experts group,Discrete cosine transformation

论文评审过程:Received 30 June 2003, Revised 28 November 2003, Accepted 28 November 2003, Available online 31 January 2004.

论文官网地址:https://doi.org/10.1016/j.imavis.2003.11.008