Quadtree classified vector quantization based image retrieval scheme

Hsin-Hui Chen, Hsin‐Teng Sheu, Jian–Jiun Ding · 2011

With the fast development of multimedia, it is crucial to find the way to search image database effectively. The vector quantization (VQ) based image retrieval method is popular in recent years. In this paper, we propose the quadtree classified vector quantization (QCVQ) scheme to improve the VQ method by exploiting the visual importance of image blocks and using the edge information to describe the content of each block efficiently. Moreover, we also apply the adaptive block size. The simulation results show that, compared with the previous image retrieval algorithms using VQ and chromaticity moments (CM), our proposed scheme has obviously better average retrieval rate and higher average precision.

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