| 基于灰度空间特征的模糊C均值聚类图像分割 |
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| 引用本文： | 李云松,李明.基于灰度空间特征的模糊C均值聚类图像分割[J].计算机工程与设计,2007,28(6):1358-1360,1363. |
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| 作者姓名： | 李云松 李明 |
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| 作者单位： | 兰州理工大学,计算机与通信学院,甘肃,兰州,730050 |
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| 摘 要： | 模糊C均值(FCM)聚类算法广泛用于图像的自动分割,但是该算法没有考虑像素的灰度和空间特征,对噪声十分敏感.因此提出一种改进的算法,在传统的FCM聚类的基础上,运用邻域像素的灰度相似度和聚类分布统计来构造新的隶属函数,对图像进行聚类分割.该方法不仅有效地抑制了噪声的干扰,而且把错分类的像素很容易的纠正过来.对两种类型的含噪图像的实验结果表明该方法对噪声具有很强的鲁棒性和对像素聚类的正确性.
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| 关 键 词： | 模糊C均值 灰度相似性 邻域空间特征 图像分割 鲁棒性 基于灰度 空间特征 模糊 均值聚类 图像分割 image segmentation feature spatial gray based clustering 鲁棒性 结果 实验 含噪图像 类型 分类 干扰 方法 聚类分割 |
| 文章编号： | 1000-7024（2007）06-1358-03 |
| 修稿时间： | 2006-04-13 |
Fuzzy c-means clustering based on gray and spatial feature for image segmentation |
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| LI Yun-song,LI Ming.Fuzzy c-means clustering based on gray and spatial feature for image segmentation[J].Computer Engineering and Design,2007,28(6):1358-1360,1363. |
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| Authors: | LI Yun-song LI Ming |
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| Affiliation: | School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China |
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| Abstract: | Fuzzy c-means(FCM) clustering algorithm has been widely used in automated image segmentation.However,the conventional FCM algorithm is sensitive to noise because of taking no into account the gray and spatial information.An improved algo-rithm based on the preliminary image segmentation with the FCM cluster is proposed.The degree of gray similarity and cluster distribution statistics of the neighbor pixels are used to form a new membership function.It is not only effective to constrain the noise,but also ease to correct the misclassified pixels.Experimental results on two types of noisy images indicate that the segmentations are more accurate and robust than the standard FCM algorithm. |
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| Keywords: | fuzzy c-means gray similarity neighbor spatial feature image segmentation robust |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
