Image Segmentation with Multilevel Threshold of Gray-Level & Gradient-Magnitude Entropy Based on Genetic Algorithm
Zhenyong Fu, Junyao He, Rui Cui, Y. Xiang, Sanli Yi, Shuiyuan Cao, Y.Y. Bao, K.K. Du, Hongying Zhang, Jiachen Ren · Advances in intelligent systems research/Advances in Intelligent Systems Research · 2015
Due to consider the gray level spatial distribution information, some image segmentation technologies based on entropy threshold can enhance the thresholding segmentation performance.However, they still cannot distinguish image edges and noise well.Even though GLGM(gray-level & gradientmagnitude) entropy can effectively solve the problem, but it cannot segment effectively multi-objective and complex image.In this paper, a GLGM entropy fast segmentation method based on GA is presented by combining Real-code-GA and GLGM entropy, and the single threshold segmentation of GLGM entropy is further extended to multilevel threshold segmentation.Our method compared with GLGM entropy multi-threshold exhaustive method, the segmentation result obtained by our method is basically the same as the result obtained by exhaustive method.