An Improved Active Contours Model Without Edges Based on Chebyshev Distance
Active contour model without edges(C-V model) is a classical one in the level set segmentation methods.However,when the classical C-V model is used for image segmentation,only the homogeneity information is taken into account.This causes the C-V model to work only images with two inhomogeneous areas but often fails to correctly segment images with inhomogeneous intensity.In this paper,a new similarity based on the Chebyshev distance was introduced to the C-V model and the mean value definition of the whole image in the traditional C-V model haven been changed.The new model solves the problem that the traditional C-V model can not correctly segment images with inhomogeneous intensity.Experiments and contrast analysis evidently show: the new model can be used to segment images with inhomogeneous intensity,and is not sensitive to the noise.