| 基于混合单纯形算法的模糊均值图像分割 |
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| 引用本文： | 李艳灵,刘婷.基于混合单纯形算法的模糊均值图像分割[J].数学的实践与认识,2012,42(14):218-223. |
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| 作者姓名： | 李艳灵 刘婷 |
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| 作者单位： | 1. 信阳师范学院计算机与信息技术学院,河南信阳,464000
2. 郑州师范学院信息科学技术学院,河南郑州,450044 |
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| 基金项目： | 国家自然科学基金，河南省高校科技创新人才计划，河南省科技计划项目，河南省高校青年骨干教师资助计划 |
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| 摘 要： | 针对模糊C均值算法用于图像分割时对初始值敏感、容易陷入局部极值的问题,提出基于混合单纯形算法的模糊均值图像分割算法.算法利用Nelder-Mead单纯形算法计算量小、搜索速度快和粒子群算法自适应能力强、具有较好的全局搜索能力的特点,将混合单纯形算法的结果作为模糊C均值算法的输入,并将其用于图像分割.实验结果表明:基于混合单纯形算法的模糊均值图像分割算法在改善图像分割质量的同时,提高了算法的运行速度.
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| 关 键 词： | Nelder-Mead单纯形算法 粒子群算法 模糊C均值 图像分割 |
Fuzzy Means Image Segmentation Based on Hybridized Nelder-Mead Simplex Algorithm |
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| LI Yan-ling
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LIU Ting.Fuzzy Means Image Segmentation Based on Hybridized Nelder-Mead Simplex Algorithm[J].Mathematics in Practice and Theory,2012,42(14):218-223. |
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| Authors: | LI Yan-ling LIU Ting |
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| Institution: | 1.College of Computer and Information Technology,Xinyang Normal University,Xinyang 464000,China) (2.College of information Science and Technology,zhengzhou Normal University,Zhengzhou 450044) |
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| Abstract: | Standard fuzzy C-means algorithm is sensitive to initial data,and gets in the local optimization easily.For this reason,fuzzy means image segmentation based on hybridized Nelder-Mead simplex algorithm is proposed in this paper.Nelder-Mead simplex algorithm has the virtues of rapid searching and less calculation.The virtues of particle swarm operation algorithm is strong adaptability and better global search capability.In the new algorithm,the virtues of Nelder-Mead simplex algorithm and particle swarm operation algorithm are used and the result of hybridized Nelder-Mead simplex algorithm is regarded as the input of fuzzy C-means algorithm for image segmentation.Experimental results show that new algorithm not only has higher convergence speed,but also can achieve more robust segmentation results. |
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| Keywords: | Nelder-Mead simplex algorithm particle swarm operation fuzzy C-means image segmentation |
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