Active Contour Model Analysis And Application For Image Segmentation

The technology of image segmentation is the foundation of image identification and image understanding. As an image segmentation method guided by high-level knowledge, active contour model is a hotspot of research in the field of image processing and active vision.In this paper, the active contour model was classified as two groups—based on edges and based on regions. We mainly focus on the active contour methods respectively, from the energy function, merits and drawbacks, algorithm to experiments. In the C-V model we are interested in the segmentation region simply while the whole region was treated as the study object, which leads to a large account of computing inefficacy. So an improved elective segmentation algorithm has been proposed.The improved algorithm merely tries to segment the regions which we are interested in. The fitting item acted as the driving force in curvature motion of C-V model was treaded as the energy function. Correspondingly optimizing of the energy function transforms into solving the ordinary differential equation. So the new algorithm reduced the complicated computing, speeded up the curve evolution and segmentation while still ensured interested region segmentation accuracy.