Wavelet-Based Texture Classification and Retrieval
نویسندگان
چکیده
As digital images become more widely used, digital image analysis must find more tools to work on them. Texture analysis is a huge challenge nowadays, since simple images may be considered as a mosaic of textures separated by some boundaries. That is why both texture retrieval and classification, combined with image segmentation, may be very powerful in image analysis. Texture retrieval (ie. to find the N most similar textures to a query texture among a large set of data textures) can be used by internet applications in the general context of Content-Based Image Retrieval, whereas texture classification (ie. among N classes of textures, to select the most probable one where the query texture could lie) has a more local use, since a “class of texture” has a loose sense, depending on the application.
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