| 基于K均值聚类和数学形态学的小麦彩色图像分割 |
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| 引用本文： | 何建斌,梁威,李晓明.基于K均值聚类和数学形态学的小麦彩色图像分割[J].浙江农业学报,2011,23(4). |
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| 作者姓名： | 何建斌 梁威 李晓明 |
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| 作者单位： | 郑州轻工业学院电气信息工程学院,河南郑州,450002 |
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| 基金项目： | 河南省国际科技合作项目超级小麦种质资源创新与品种培育 |
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| 摘 要： | 对小麦植株图像进行分割,是将机器视觉技术应用到动态监测小麦生长状况的基础.采用K均值聚类和数学形态学相结合的方法进行分割,充分利用了小麦植株颜色和背景颜色的差异.首先根据图像色彩对图像进行聚类,然后对聚类后的图像进行形态学开运算,实现了小麦植株与背景的分离,并达到了较好的效果.
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| 关 键 词： | K均值聚类 数学形态学 L*a*b*色彩空间 |
The color image segmentation of wheat based on K-means clustering and mathematical morphology |
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| HE Jian-bin,LIANG Wei,LI Xiao-ming.The color image segmentation of wheat based on K-means clustering and mathematical morphology[J].Acta Agriculturae Zhejiangensis,2011,23(4). |
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| Authors: | HE Jian-bin LIANG Wei LI Xiao-ming |
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| Institution: | HE Jian-bin,LIANG Wei,LI Xiao-ming(College of Electric and Information Engineering,Zhengzhou University of Light Industry,Zhengzhou 450002,China) |
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| Abstract: | Wheat image segmentation is the basic work of applying computer vision technology to dynamic monitoring wheat growing.This paper proposed an algorithm combining K-means clustering and mathematical morphology which full use of the color differences between wheat plant and background in the image.Firstly,clustering image based on colors,and then mathematical morphology opening operation was used to eliminate noise.Experiment results showed that the algorithm was effective in segmenting wheat color images. |
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| Keywords: | K-means clustering mathematical morphology L*a*b* color space |
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