| 基于PSO与K-均值算法的农业超绿图像分割方法 |
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| 引用本文： | 赵博,宋正河,毛文华,毛恩荣,张小超.基于PSO与K-均值算法的农业超绿图像分割方法[J].农业机械学报,2009,40(8). |
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| 作者姓名： | 赵博 宋正河 毛文华 毛恩荣 张小超 |
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| 作者单位： | 1. 中国农业机械化科学研究院,北京,100083
2. 中国农业大学工学院,北京,100083 |
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| 基金项目： | 国家自然科学基金资助项目，国家"863"高技术研究发展计划资助项目，"十一五"国家科技支撑计划资助项目 |
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| 摘 要： | 为了解决K-均值算法对农业图像中常用的超绿特征2G-R-B图像分割效果不佳的缺点,提出一种基于微粒群与K-均值算法的图像分割方法.先用K-均值算法对图像进行快速分类,然后将分类结果作为其中一个微粒的结果,利用微粒群算法计算,最后用K-均值算法在新的分类基础上计算新的聚类中心,更新当前的位置.以得到最优的图像分割闽值.试验结果表明,改进算法对超绿特征2G-R-B图像能够准确分割目标,且对不同类型的农业超绿图像具有较好的适应性.
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| 关 键 词： | 图像分割 微粒群算法 K-均值算法 超绿特征 |
Agriculture Extra-green Image Segmentation Based on Particle Swarm Optimization and K-means Clustering |
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| Zhao Bo,Song Zhenghe,Mao Wenhua,Mao Enrong,Zhang Xiaochao.Agriculture Extra-green Image Segmentation Based on Particle Swarm Optimization and K-means Clustering[J].Transactions of the Chinese Society of Agricultural Machinery,2009,40(8). |
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| Authors: | Zhao Bo Song Zhenghe Mao Wenhua Mao Enrong Zhang Xiaochao |
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| Institution: | 1.Chinese Academy of Agricultural Mechanization Sciences;Beijing 100083;China2.College of Engineering;China Agricultural University;China |
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| Abstract: | In order to solve the disadvantage of image segmentation by K-means clustering to extra-green character used to be adopted in agricultural images,an image segmentation method based on the particle swarm optimization and the K-means clustering was proposed.Firstly,image pixels value was fast clustered with the K-means clustering.Regarding the results as the position of a particle,PSO can be used and the new class centers also can be re-calculated with the K-means clustering.Subsequently,the position of all p... |
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| Keywords: | Image segmentation Particle swarm optimization K-means clustering Extra-green character |
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