An Improved Feature Vector for Content-based Image Retrieval in DCT Domain

Cong Bai, Kidiyo Kpalma, Joseph Ronsin

Abstract

This paper proposes an improved approach for content-based image retrieval in Discrete Cosine Transform domain. For each 4x4 DCT block, we calculate the statistical information of three groups of AC coefficients and propose to use these values to form the AC-Pattern and use DC coefficients of neighboring blocks to construct DC-Pattern. The histograms of these two patterns are constructed and their selections are concatenated as feature descriptor. Similarity between the feature descriptors is measured by c2 distance. Experiments executed on widely used face and texture databases show that better performance can be observed with the proposal compared with other classical method and state-of-the-art approaches.

References

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Paper Citation


in Harvard Style

Bai C., Kpalma K. and Ronsin J. (2013). An Improved Feature Vector for Content-based Image Retrieval in DCT Domain . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1, pages 742-745. DOI: 10.5220/0004206607420745


in Bibtex Style

@conference{visapp13,
author={Cong Bai and Kidiyo Kpalma and Joseph Ronsin},
title={An Improved Feature Vector for Content-based Image Retrieval in DCT Domain},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={742-745},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004206607420745},
isbn={978-989-8565-47-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)
TI - An Improved Feature Vector for Content-based Image Retrieval in DCT Domain
SN - 978-989-8565-47-1
AU - Bai C.
AU - Kpalma K.
AU - Ronsin J.
PY - 2013
SP - 742
EP - 745
DO - 10.5220/0004206607420745