NEW ALGORITHM OF MULTISCALE TEXTURE IMAGE SEGMENTATION BASED ON CONTOURLET TRANSFORM

A new feature extraction method, finite texture mixture pattern (FTMP), was proposed inspired by the basic idea of pattern-based texture analysis methods. FTMP was a two-tuplet set, which could be obtained by clustering methods. Firstly, the multi-scale and multi-direction variations were calculated based on the Contourlet transform. Secondly, these variation information at different scale and in different direction were clustered into groups respectively. The centers and their corresponding proportion made up FTMP, which reflected the primary information's variations of different scales and different directions. Such a feature extraction method made full use of the idea of pattern-based method, but avoided the complicated parameter estimation and expression computation. Thus a supervised multi-scale texture image segmentation algorithm based on Contourlet transform-CFTMPseg was proposed based on FTMP, and its effectiveness was proven by quantitative and qualitative experiments.