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Content-based image retrieval (CBIR), DWT, Region-based image retrieval (RBIR), SA-DWT
In this paper, we present an efficient region-based image retrieval method, which uses multi-features color, texture and edge descriptors. In contrast to recent image retrieval methods, which use discrete wavelet transform (DWT), we propose using shape adaptive discrete wavelet transform (SA-DWT). The advantage of this method is that the number of coefficients after transformation is identical to the number of pixels in the original region. Since image data is often stored in compressed formats: JPEG 2000, MPEG 4…; constructing image histograms directly in the compressed domain, allows accelerating the retrieval operation time, and reducing computing complexities. Moreover, SA-DWT represents the best way to exploit the coefficients characteristics, and properties such as the correlation. Characterizing image regions without any conversion or modification is first addressed. Using edge descriptor to complement image region characterizing is then introduced. Experimental results show that the proposed method outperforms content based image retrieval methods and recent region based image retrieval methods.
Lakhdar BELHALLOUCHE, Kamel BELLOULATA, Kidiyo KPALMA,"A New Approach to Region Based Image Retrieval using Shape Adaptive Discrete Wavelet Transform", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.8, No.1, pp.1-14, 2016. DOI: 10.5815/ijigsp.2016.01.01
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