A maximum likelihood approach to texture classification using wavelet transform
K. S. Thyagarajan, Trung Quoc Nguyen, C.E. Persons · 2002
The paper describes a method of classifying natural textures based on maximum likelihood parameter estimation technique. The wavelet transform (WT) is used to represent the textural images in multiresolution. Co-occurrence matrices are then computed for the different scales of the wavelet transform and textural features are obtained from the co-occurrence matrices. Then a maximum likelihood classifier is designed using a set of training texture samples. Ten different Brodot textures have been classified using this procedure with an average classification accuracy of 99.7.>