| 改进的K-均值聚类算法图像边缘检测研究 |
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| 引用本文： | 张菊.改进的K-均值聚类算法图像边缘检测研究[J].科技通报,2012,28(6):47-48. |
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| 作者姓名： | 张菊 |
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| 作者单位： | 辽宁省交通高等专科学校,沈阳,110122 |
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| 摘 要： | 图像边缘检测一直是图像处理领域研究的重点问题。边缘是图像最基本的特征,本文采用了模糊K-均值聚类算法对图像进行边缘检测。该方法针对不同的图像找到相对比较有效的边缘检测算法,进而大幅度地减少了数据量,保留了图像重要的结构属性。通过mat lab实验,证明了该方法可以有效提取图像的边缘信息。
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| 关 键 词： | 图像处理 边缘检测 K-均值聚类 |
Image Edge Detection Based on the Improved K- means Clustering Algorithm |
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| ZHANG Ju.Image Edge Detection Based on the Improved K- means Clustering Algorithm[J].Bulletin of Science and Technology,2012,28(6):47-48. |
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| Authors: | ZHANG Ju |
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| Institution: | ZHANG Ju(Liaoning Provincial College of Communications,Shenyang 110122,China) |
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| Abstract: | The image edge detection is always the focus of the research field of image processing.Edge is the most basic features of the image,this paper used K-means clustering algorithm for image edge detection,the method according to the different image to find relatively effective edge detection algorithm,which greatly reduces the amount of data,the image retains the important structural properties,through MATLAB experiments proved that the method can effectively extract the image edge information. |
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| Keywords: | image processing edge detection K-mean clustering |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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