Research Of Image Segmentation Algorithm

Image segmentation partitions an image into different regions with some specific properties. Segmentation is one of the most difficult and important steps in digital image processing. Segmentation accuracy determines the eventual success or failure of computerized analysis procedures. For this reason, image segmentation has been widely investigated and hundreds of algorithms have been presented in the literature. Although those algorithms are to some extent successful, image segmentation is still far from been solved. Due to the lack of systematic theory,there is no idea to guide us how to choose appropriate algorithms for different images. There is no single method which can be considered good for all images,and a universally accepted technique for evaluation of segmentation results is not existed. This paper studies the classic segmentation methods, presents the direction of segmentation algorithms, and gives a method based on mathematical morphology and fuzzy theory.1 Based hundreds of algorithms presented in the literature, this paper classify image segmentation algorithms into three categories: methods based edge, methods based region, methods based special theories. Some common and classic algorithms belonging to the categories respectively are introduced.2 The algorithms based thresholding and the basic theory of watershed methods are introduces detail. A watershed method is improved though reconstruct grads graphic by using maker restrictions.3 This paper expatiates clustering analysis and fuzzy clustering method. An improved method based mathematical morphology and fuzzy clustering method is proposed. Using this method to segment an infrared image gets well results.