Decision Support System Including Fuzzy Logic and Multi-resolution Wavelet Network Modeling For Content-based image retrieval

In this paper, we propose a new structure of indexing and images retrieval process based on feature extraction by multi-resolution wavelet network (MRWN) modeling and a Fuzzy Decision Support System (FDSS) for measuring similarity. First, each query image is modeled by a MRWN of hybrid and optimal architecture, then, for the determination of visual characteristics called low levels, this network is used. The moments calculated using detail weights of the MRWN for different levels will form together the shape descriptor while the energies of the approximation weights are computed to determine texture descriptor. The FDSS is used to determine the closest benchmark images to the query image in term of texture and shape. Sorting images is then performed by a proposed algorithm measuring the degree of similarity in color between the query image and the images resulted from the decision by fuzzy logic.

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