A New Multiscale Segmentation Algorithm on Texture Image in Wavelet Domain

With the illumination of the basic idea of model-based texture analysis methods, a new feature extraction method, Finite Texture Mixture Pattern (FTMP), was proposed in this paper. FTMP is a two-tuplet set, which can be obtained by the clustering methods. Firstly, the multi-scale and multi-direction variations are calculated. Secondly, these variations of each scale are clustered into groups respectively. The centers and their corresponding proportions composite FTMP, which describes the primary variations of different scales and different directions. Such a feature extraction method takes full advantage of the idea of model-based method, but avoids the complicate parameter estimation and expression computation. Based on FTMP, a supervised multi-scale texture image segmentation algorithm-FTMPseg is proposed, and its effectiveness is proven by quantitative and qualitative experiments.