Content-based image retrieval through compressed indices based on vector quantized images

Chia-Hung Yeh; Chung J. Kuo

doi:10.1117/1.2150793

1 January 2006 Content-based image retrieval through compressed indices based on vector quantized images

Chia-Hung Yeh, Chung J. Kuo

Author Affiliations +

Optical Engineering, Vol. 45, Issue 1, 017001 (January 2006). https://doi.org/10.1117/1.2150793

Abstract

A multimedia database system should deal efficiently with both image compression and retrieval functions. It is critical to develop image indexing techniques that search databases based on their content in a compressed domain. We propose a new scheme, query by index image, based on vector quantization, to facilitate image retrieval in a compressed domain. The proposed algorithm exploits different index images obtained by sorting codevectors to capture various kinds of image feature. Hence, intrablock correlation and interblock correlation in an image can be efficiently represented. Our proposed algorithm not only can extract features from the pixel domain but also from a transform domain, such as that of wavelet coefficients. Experimental results demonstrate that the retrieval performance of the proposed scheme is more accurate than that of other similar methods.

©(2006) Society of Photo-Optical Instrumentation Engineers (SPIE)

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Chia-Hung Yeh and Chung J. Kuo "Content-based image retrieval through compressed indices based on vector quantized images," Optical Engineering 45(1), 017001 (1 January 2006). https://doi.org/10.1117/1.2150793

Published: 1 January 2006

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