Good Effect of GVF Snake Segmentation By Good Parameters Settings
the basic theory and the key algorithm about GVF Snake model are presented firstly. Then a lot of important experiments are done to achieve the effect of the GVF Snake segmentation about stomach epidermis tumors after having set the values of some important parameters in GVF Snake model. Firstly, the effect of two kinds image pretreatment processing such as the edge mapping and the gauss blur are analyzed, and the conclusion is found that the edge mapping must be run before the GVF Snake segmentation. Otherwise the snake can only converge to one point instead of the edge of the cells. Moreover, good image segmentation result will be attained if the gauss blur which restrains the noise of an image has been run before the edge mapping. Flexible parameter α and rigid parameter β are also analyzed by experiments, which prove that the snake model cannot get good convergence result if α is less than 1 and much smaller areas may be got if α is higher than 1.Furthermore, parameter β doesnt work in any experiments. At the same time, iteration times of GVF Snake are analyzed too. The segmentation result becomes stable if the iteration times is bigger than 80 in these experiments. Finally, it is proved that good segmentation results can be got if μ is less than 0.3.
GVF Snake image segmentation gauss blur edge mapping flezible parameter α rigid parameter β iteration times pretreatment processing
Li Guangli Zhang Hongbin
School of Information Engineering East China Jiaotong University Nanchang,China
国际会议
北京
英文
1-5
2009-06-11（万方平台首次上网日期，不代表论文的发表时间）