An image segmentation algorithm based on combination of slope width reduction and cross cortical model

Abstract

An image segmentation algorithm based on the ramp width reduction combined with an Intersecting Cortical Model (ICM) is proposed against problems that ICM in the segmentation of image with weak edge produces geometric distortion. By virtue of prewitt boundary operator and edge ramp model, the algorithm defines the objective edge point, adjusts the grey level of edge pixel, and reduces the width of image edge. On this basis, the paper uses 2D histogram to expand the cross entropy to 2D space so as to obtain the optical segmentation threshold of ICM. The experiment indicates that the algorithm not only overcomes the impact of edge blur and segment the image with weak edge accurately, but also improves the processing speed greatly.