The Research Of Image Edge-detection Method In The Surgery Simulation System

Edge detection is an indispensable step before image analysis and recognition, and is an important technology in the image preprocessing procedure. To the surgery simulation system, the edge-detection of the human body section image is a crucial process too.This thesis discusses the edge-detection method based on the wavelets analysis, and the GVF (Gradient Vector Flow) Snake deformable model. The thesis modifies some shortages of the two methods. And based on the advantages of the two edge detection methods, a new edge-detection deformable model is put forward: WVF (Wavelets Vector Flow) Snake model.The main achievements of this thesis are as following:1. The thesis analyzes and realizes the traditional edge detection method that based on the differential operator and based on the wavelets transform. The method of wavelets transform has some shortcoming such as the edge is disconnected and is not single. To this, the thesis put forward modified algorithm.2. GVF Snake model is an efficient method for contour detection of objects on an image. In the thesis, a detailed analysis of GVF Snake model is given with emphasis on its limitations and shortcomings, and then the model is improved and a new method is proposed. The new GVF Snake model can solve the problems that the GVF Snake model can not detect the edges like a bottle.3. Based on the analysis of the GGVF (Generalized Gradient Vector Flow) Snake model, one of its shortcomings is pointed out. To the long, thin boundary indentation of the images, if the number of the indentation's pixel is even number, the GGVF Snake model can not approach the edge. Through the disposal to the force field, the modified method is put forward.4. A new images edge-detection method is put forward: WVF (Wavelets Vector Flow) Snake model. The method solves the problem that the edge based on the wavelets method isn't consecutive. It develops the GVF Snake model's ability that withstands the images' noises. The experience indicates that the new method can develop snake model's ability to manage the complicated images.