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7 May 2003 Texture-based image retrieval using multiscale subimage matching
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The paper presents research on a robust technique for texture-based image retrieval in multimedia museum collections. The aim is to be able to use a query image patch containing a single texture to retrieve images containing some area with similar texture to that in the query. A retrieval technique without the need for segmentation is presented. The algorithm uses a multiscale sub-image matching method together with an appropriate texture feature extractor. The multiscale sub-image matching is achieved by first decomposing each database image into a set of 64×64 pixel patches covering the entire image. The resolution of the database image is then rescaled to create sub-images corresponding to a larger scale. The process continues until the final resolution of the image is equal to some pre-determined value. Finally, a collection of sub-images corresponding to different image regions and scales is obtained. The final image feature vector consists of a collection of feature vectors corresponding to each sub-image. Several wavelet-based feature extractors are tested with the multiscale technique. From the experiments, it is found that the multiscale sub-image matching method is an efficient way to achieve effective texture retrieval without any need for segmentation.
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Mohammad F. A. Fauzi and Paul H. Lewis "Texture-based image retrieval using multiscale subimage matching", Proc. SPIE 5022, Image and Video Communications and Processing 2003, (7 May 2003);

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