ACTIVE CONTOUR MODEL BASED ON MULTI SCALE IMAGE ANALYSIS

Active contour model is a widely used algorithm to track object contours in the field of digital image processing. But in the practice of application, the present models often subject to the influence of noises and fake edges, and their abilities of searching concave contour are not good. Based on the multi scale image analysis, the concept of gradient vector flow （GVF） is introduced and its algorithm is improved to present a new active contour model. The new model uses the forces produced by GVF to search object contours through the scale space of an image. It can efficiently get rid of the influence of noises and search concave contours. Furthermore, it is convenient to add new constraints to the model. Experiments prove that the new model is robust and practicable, and it is suited for searching concave or convex contours against contaminated background.