Performance comparison of JPEG compressed domain image retrieval techniques

Although content-based image retrieval (CBIR) has been an active research area for more than two decades, relatively little work takes into account that virtually all images exist in compressed form, mostly in (lossy) JPEG format. In this paper, we benchmark eight state-of-the-art CBIR algorithms th...

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Bibliographic Details
Published in2012 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC) pp. 587 - 592
Main Authors Edmundson, David, Schaefer, Gerald
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 01.08.2012
Subjects
compressed domain image retrieval
Content-based image retrieval
Discrete cosine transforms
Feature extraction
Histograms
Image coding
Image color analysis
image compression
Image retrieval
JPEG
Transform coding
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Summary:Although content-based image retrieval (CBIR) has been an active research area for more than two decades, relatively little work takes into account that virtually all images exist in compressed form, mostly in (lossy) JPEG format. In this paper, we benchmark eight state-of-the-art CBIR algorithms that operate directly in the compressed domain of JPEG by performing retrieval based on DCT coefficients. We analyse their performance on a benchmark dataset, compare them against common pixel-domain techniques, investigate whether they are affected by compression ratio, and measure their computational complexity. We conclude that several of the JPEG CBIR techniques allow much faster feature calculation and faster image retrieval, while providing retrieval performance similar to common pixel-domain algorithms.
ISBN:9781467321921
1467321923
DOI:10.1109/ICSPCC.2012.6335725