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Exploiting image indexing techniques in DCT domain
Author(s) -
ChongWah Ngo,
Ting-Chuen Pong,
R.T. Chin
Publication year - 1998
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
DOI - 10.1007/bfb0016499
Subject(s) - discrete cosine transform , computer science , search engine indexing , artificial intelligence , block (permutation group theory) , jpeg , pattern recognition (psychology) , image retrieval , computer vision , image texture , image processing , texture (cosmology) , image (mathematics) , mathematics , geometry
This paper is concerned with the indexing and retrieval of images based on features extracted directly from the JPEG discrete cosine transform (DCT) domain. We examine possible ways of manipulating DCT coe$cients by standard image analysis approaches to describe image shape, texture, and color. Through the Mandala transformation, our approach groups a subset of DCT coe$cients to form ten blocks. Each block represents a particular frequency content of the original image. Two blocks are used to model rough object shape; nine blocks to describe subband properties; and one block to compute color distribution. As a result, the amount of data used for processing and analysis is signi"cantly reduced. This can lead to simple yet e$cient ways of indexing and retrieval in a large-scale image database. Experimental results show that our proposed approach o!ers superior indexing speed without signi"cantly sacri"cing the retrieval accuracy. 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

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