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.<>
A maximum likelihood approach to texture classification using wavelet transform
Proceedings of 1st International Conference on Image Processing ; 2 ; 640-644 vol.2
1994-01-01
420444 byte
Conference paper
Electronic Resource
English
A Maximum Likelihood Approach to Texture Classification using Wavelet Transform
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