A comparative study of filter based texture operators using Mahalanobis distance

Texture feature extraction operators, which comprise linear filtering, eventually followed by post-processing, are considered. The filters used are Laws´ masks (1980), filters derived from well-known discrete transforms, and Gabor filters. The post-processing step comprises nonlinear point operations and/or local statistics computation. The performance is measured by means of the Mahalanobis distance between clusters of feature vectors derived from different textures. The results show that post-processing improves considerably the performance of filter based texture operators