Content-based Image Segmentation Using Deformable Template Matching
Xue Zhao · Dianzi xuebao · 2000
A novel method of content based image segmentation using deformable template matching is proposed.A two dimensional (2 D) deformable template based on orthogonal curves is built by pre computing extensions of the deformable template along orthogonal curves and sampling the curves uniformly.Then the definitions of internal and external energy functions are given according to the image segmentation problem,and genetic algorithm is used to obtain globally optimal solutions.The proposed method uses a lower dimensional search space than conventional methods and reduces the sensitivity of the algorithm to initial placement of the template.Experiments on real world images and in simulations at low signal to noise ratio show the robustness and good performance of the method.