Image Color Segmentation Based on QPSO Algorithms
基于QPSO算法的图像颜色分割

At present, Segmentation of a color image composed of different kinds of texture regions is still a difficulty. Computing the exact texture fields and the optimum number of segmentation areas in an image is difficult, when it contains similar and/or unstationary texture fields. In this paper, describing image color segmentation by QPSO. We formulate the segmentation problem upon such images as an optimization problem and adopt evolutionary strategy of QPSO for the clustering of regions in color feature. Not only parameters of QPSO are few and randomicity of QPSO is strong, but also QPSO covers with all solution space and guarantee global convergence of algorithms. Three images results of segmentation are presented and demonstrate the efficiency of QPSO algorithms to automatic and unsupervised texture segmentation.