Segmentation of Multi-Channel Image with Markov Random Field Based Active Contour Model

摘要

Segmentation is an important research area in image processing and computer vision. The essential purpose of research work is to achieve two goals: (i) partition the homage into homogeneous regions based on certain properties, and (ii) accurately track the boundary for each region. In this study, we will present a novel framework that is designed to fulfill these requirements. Distinguished from most existing approaches, our method consists of three steps in the segmentation processes: global region segmentation, control points searching and object boundary tracking.