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Texture describes the content of many real world images: for example, clouds, trees, bricks, hair, fabric etc. all of which have textural characteristics.Feature extraction is one of the most important tasks for efficient and accurate image retrieval purpose. In this book we are going to use Cosinemodulated wavelet transform based technique for extraction of texture features. The major advantages of Cosinemodulated wavelet transform are less implementation complexity, good filter quality, and ease in imposing the regularity conditions. Texture features are obtained by computing the energy, standard deviation and their combination on each subband of the decomposed image. To check the retrieval performance, texture database of 1856 textures is created from Brodatz album. Retrieval efficiency and accuracy using Cosinemodulated wavelet based features will be found to be superior to other existing methods.
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