Extremum Of The Functional-based Image Segmentation Algorithm

This paper chooses algorithm of image segmentation based on functional extreme as its research subject.First of all, the classical Otsu algorithm is taken for the research of algorithm based on Exhaustive Attack searching and functional extreme. Throuth the investigation of a deficiency of speed, the affection from Exhaustive Attack searching to the operation quantity of the algorithm is analysed, and this draw forth the second stage of a research of algorithm based on Intelligence Optimum Algorithm and functional extreme which conclude the originality of this paper. In this stage two tactics is proposed, that is an injection of simulated annealing and also an injection of metempirical classification information of images. This makes a chage for increase of operation quantity as the number of threshold from geometric progression to analogous linear progression. Then the research is carried out with algorithm based on variations, named deformable contour models. Two kinds of deformable model algorithms are studied, and more research are done on two typical models which differ in the function i.In this paper in order to conquer the problem of mis-segmentation of partial region, a method of using mutual information to construct a new functional is proposed.Experiment results of Otsu and the processed algorithm has been discussed on matlab 701, and also the result of the method based on mutual information and deformable contour models are analysed.