This paper presents a technique for texture feature extraction and classification using wavelet transform. A image is
decomposed into no. of sub-bands after applying Wavelet transform to it. A three level decomposition is carried out. A
number of sub-bands are generated after wavelet decomposition. An energy signature is computed for each sub-band of
these wavelet coefficients. A k-nearest neighbor's classifier is then employed to classify texture patterns. To test and
evaluate the method, several sets of textures along with different wavelet bases are employed. Experimental results show
superiority of the proposed method.
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