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A large number of algorithms have been proposed to retrieve and analyze texture images. While much effort has been made to find algorithms applicable to all textures for superior retrieval performance, less work has been done to adaptively integrate various texture retrieval and analysis algorithms. As no individual texture retrieval algorithm is suited for every texture category, a hybrid scheme would outperform any individual method. In this paper, an adaptive retrieval scheme (ARS) for texture image indexing is proposed to dynamically adapt different transforms to different texture patterns for better retrieval performance. The experiments on the Brodatz texture database show that ARS significantly outperforms any individual transform.