| 基于混沌粒子群优化算法的二维熵图像分割方法 |
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| 引用本文： | 黄力明. 基于混沌粒子群优化算法的二维熵图像分割方法[J]. 陕西理工学院学报(自然科学版), 2007, 23(4): 47-51 |
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| 作者姓名： | 黄力明 |
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| 作者单位： | 镇江高等专科学校,电子信息系,江苏,镇江,212003 |
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| 摘 要： | 针对二维熵图像分割方法在求取最佳阈值时存在计算量大及微粒群算法容易陷入局部最优且速度较慢等等问题,提出了基于混沌粒子群优化算法的二维熵图像分割方法。该方法考虑了图像中像素点灰度——邻域灰度均值对作为阈值对图像进行分割;利用混沌运动随机性、遍历性和初值敏感性,将混沌粒子群优化算法与阈值法相结合在二维空间作全局搜索。实验结果表明了基于混沌粒子群优化算法的二维熵图像分割法用于阈值寻优减少了搜索时间,提高了收敛率。
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| 关 键 词： | 图像分割 粒子群优化算法 阈值 混沌 |
| 文章编号： | 1673-2944（2007）04-0047-05 |
| 修稿时间： | 2007-03-20 |
2-D entropy method of image segmentation based on chaotic particle swarm optimization algorithm |
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| HUANG Li-ming. 2-D entropy method of image segmentation based on chaotic particle swarm optimization algorithm[J]. Journal of Shananxi University of Technology(Natural Science Edition), 2007, 23(4): 47-51 |
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| Authors: | HUANG Li-ming |
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| Affiliation: | Department of Electronics and Information, Zhenjiang College, Zhenjiang 212003, China |
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| Abstract: | To the problems of the 2-D maximum entropy image segmentation method is computationally expensive and Particle Swarm Optimization algorithm is easy to fall into local optimum and also the speed is slow,2-D Entropy Method of Image Segmentation Based on Chaotic Particle Swarm Optimization algorithm is proposed to solve the optimization problems.By using the properties-ergodicity,randomicity,and regularity of chaos,Chaotic Particle Swarm Optimization algorithm is combined with thresholding methods.The experimental result indicates 2-D Entropy Method of Image Segmentation Based on Chaotic Particle Swarm Optimization algorithm reduces the searching time significantly enhances the convergency factor. |
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| Keywords: | image segmentation particle swarm optimization algorithm threshold chaos |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
