Study Of Image Segmentation And Object Contour Tracking Based On Snake Models

Snake model is widely used in the domain of medical image segmentation, videoanalysis and so on. Though being studied for more than 20 years, there are still someproblems to be solved. This dissertation focused on three of the problems: the segmen-tation result of snake is heavily sensitive to the initial contours, the snake model is notappropriate for automatic segmentation, and the low computation velocity of geometricsnake. And three new methods are proposed.1. A new external force field named adaptive pressure force field which makesthe snake model not sensitive to the position of initial curve is proposed. First, theinitial problem of snake model is studied. Based on the analysis of and comparisonamong the existing external force such as balloon model, gradient vector ?ow and soon, the character of an external force which can avoid the sensitiveness to the positionof initial curve is concluded: the pressure force imposed on the snake model should beable to change adaptively according to its position, namely, it can drive the snake modelto in?ate when the evolution curve locates inside the region of the object and shrinkwhen the curve locates outside. Then, according to the character of adaptive pressureforce field, two method are proposed to construct such force field. One is based on theneighborhood, and the other is based on gradient. The time complexity of the formeris high, but it can get very good result by choosing appropriate size of neighborhood ifthe object to be segmented is thin. The latter can be calculated fast, so it can be widelyused.2. A fast automatic image segmentation method is proposed by the integrationof the external force field of snake model and seeded region growing method. Theexistence of human interaction makes snake model not appropriate for the domain ofautomatic segmentation. So the automatic segmentation method need to be studied.According to the theory of ?ow field analysis, the characteristic of each point in thefield can be re?ected by the directions of the vectors around it. Thus, an assistant image called ?ow direction scalar field is acquired by mapping the directions of thevectors of each point to be a scalar. Then the scalar field is segmented by using animproved seeded region growing method to get the initial segmentation result. And thefinal result is acquired by a region merging step. The proposed method is very e?cient,robust to noise and fit for the fast application. Besides, it is extended to the domain ofcolor-texture image segmentation.3. A video object contour tracking method based on dual-front snake model is pro-posed. Comparing with the parametric snake, geometric snake has better performance.But it is di?cult to be used in the domain of object tracking which need a high pro-cessing speed because of its heavy computation load. Two adapt the original dual-frontactive contour to object contour tracking, two improvements called support region re-striction and quasi-balloon model are made, thus a new model named dual-front snakewith quasi-balloon is acquired. Then a fast and ?exible contour tracking method isproposed based on the new model. The method is applicable for tracking fast movingobject and deformable object, and no static background is assumed. In addition, themodel can control the topology change adaptively as other geometric snakes.