Abstract

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.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call