Texture Analysis and Segmentation Using Dominant Component Analysis

Texture analysis in computer vision aims at the problems of feature extraction, segmentation and classification, synthesis, and inferring shape from texture. The main objective of this project is to analyze the texture and segment it using textur models. The three stages in this project are texture analysis, edg detection and segmentation. In the first stage, to extract feature, w propose a Regularized Demodulation Algorithm which provides more robust texture features. Second stage is edge detection that facilitates the estimation of posterior probabilities for the edge and texture classes. Third is segmentation that is based on DCA features which uses curve evolution implemented with level set methods With DCA a low-dimensional, yet rich texture feature vector that proves to be useful for texture segmentation.