Research On Technology Of Image Segmentation Based On Level Set Method

Image segmentation is often used as a basic image processing operation, the segmentation result is directly related to the follow higher level of image processing and computer vision work. The appearance of level set brings strong vitality to active contour model, a lot of classic contour mode also arise from this. The level set method can implicitly describe the curve evolution, it can overcome many inherent defects of parametric Snake Model and automatically deal with the changes of curve topology in evolution, this makes the application of active contour model greatly expanded. This article will study the application of level set curve evolution theory in the image segmentation, and how to construct a new active contour model with more superior performance. This article could be divided into three parts:First, we have studied the level set method's application and algorithm in the area of the curve evolution theory, and studied active contour models'development and classical model based on the level set model. Using level set method to describe the curve evolution implicitly can automatically handle the changes in its topology, this produces some excellent geometric active contour models. This article describes numerical calculation methods and some good performance fast algorithm and initialization algorithms of the level set method's. This paper also introduces some classic active contour model based on level set methods in detail, experimentalize on these models, and analyzes some inherent advantages and disadvantages of the related models.Second, we studied the image denoising methods based on partial differential equations, with integrating the image denoising methods with the image segmentation methods based on the level set methods, we proposed a new model for image segmentation. Noise pollution in the image will bring an error in the process of image segmentation, therefore, this paper researched some more superior denoising methods based on partial differential approach, then proposed a new image denoising method based on higher order. This denoising methods and the level set based image segmentation methods was integrated in the paper, the purpose of the integration is to use each other's results mutually in the process of image segmentation and image denoising, then proposed a segmentation method basing on the methods of image denoising and the level set.Finally, this article researched the image segmentation methods based on fuzzy theory, applied the fuzzy theory to image segmentation model basing on the level set methods, proposed a active contour model with fuzzy weights. The purpose is to make the image segmentation method which based on information of the regional can reach the global optimum and can be applied to segmentation of the image which has some pixels of unclear category.