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DOI:
计算机系统应用英文版:2012,21(2):188-191
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K-均值聚类算法在电容器外观图像分割中的应用
(中南大学 物理科学与技术学院,长沙 410083)
Application of K-Means Clustering Algorithm to Capacitor Appearance Image Segmentation
(School of Physics Science and Technology, Central South University, Changsha 410083, China)
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Received:May 19, 2011    Revised:June 11, 2011
中文摘要: 电容器是电子整机产品的必要器件。由于制造工艺及设备水准的限制,露白是一种常见的电容器外观缺陷。基于K-均值聚类算法,结合露白电容器外观图像的特点,提出了电容器露白区域分割算法。根据Ohta 等人的研究成果,选取能有效表示彩色特征的彩色特征集中的第一个分量,用来替代K-均值聚类图像分割中的灰度;确定分类类别数为两类,采取了粗糙集理论的算法,求出初始聚类中心和间距阈值。实验表明,该图像分割算法能有效分割出电容器图像的露白区域,具有较好的精确度和准确度。
中文关键词: 电容器  K-均值  粗糙集  图像分割
Abstract:Capacitor is the necessary component of electronic whole products. Because of manufacturing technology and the limit of equipment's level, the thief is a common capacitor cosmetic defects. This paper puts forward a regional segmentation algorithm of the thief capacitor based on the k-means clustering algorithm and combining the characteristics of the image of the thief capacitor. According to the research results of Ohta, et al, the first component of color feature is chosen and used as the image segmentation by employing the K-means clustering method. This paper defines the number of classification is two, and gives the algorithm of initial clustering center and spacing threshold according to rough set theory. Experimental results show that this image segmentation algorithm can effectively segment the thief area of the capacitor image, and have good precision and accuracy.
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孙克辉,洪天勤.K-均值聚类算法在电容器外观图像分割中的应用.计算机系统应用,2012,21(2):188-191
SUN Ke-Hui,HONG Tian-Qin.Application of K-Means Clustering Algorithm to Capacitor Appearance Image Segmentation.COMPUTER SYSTEMS APPLICATIONS,2012,21(2):188-191