摘要
为了在嵌入式系统中实现对零件的有效分类,针对机械零件边缘特征比较明显的特点,提出了一种机械零件图像边缘特征的提取方法。首先采用K irsch算子提取零件二值图像的边缘,然后以零件质心为中心将边缘图像划分为若干个子区域,并对各子区域分别计算出其修正的归一化中心矩,并将以此形成的行向量作为零件分类识别的特征。实验分析中采用K均值聚类算法对提取的零件边缘特征进行分类,实验结果验证了该方法的有效性。
In order to effectively classify mechanical components in embedded system,a novel method was proposed to extract edge features of mechanical component images since mechanical components have comparatively obvious edge features.First,the Kirsch operator was used to extract the edge of mechanical component binary image.Then the edge image was divided into several areas with the centroid as the center,and the modified normalized central moments of each area were calculated.The vectors including these central m...
出处
《四川大学学报(工程科学版)》
EI
CAS
CSCD
北大核心
2008年第5期181-184,共4页
Journal of Sichuan University (Engineering Science Edition)
基金
国家自然科学基金资助项目(59975063)
关键词
零件图像
边缘特征
中心矩
均值聚类算法
mechanical components image
edge feature
central moment
means clustering algorithm