Wavelet domain features for texture description, classification and replicability analysis

In this paper we present a new wavelet domain technique for texture analysis and test of pattern replicability. The main property of the proposed features is that they measure texture quality along the most important perceptual dimensions. In other words, we quantify and classify textures according to their directionality, symmetry regularity and type of regularity. After the feature extraction, texture classification is performed by traversing a tree. The algorithm is tested on a database with 340 images demonstrating an excellent classification accuracy.