摘要
工业CT技术能准确地重建出工件内部结构的灰度图像,这为无损检测工件内部装配缺陷(漏装、误装和多装等)提供了可能。提出一种新的模板匹配算法来实现装配缺陷的检测。首先,利用模板的平均灰度矢量进行粗搜索,确定出候选匹配点集;其次,利用模板的Zernike矩进行精搜索,定位出目标。实验结果表明,即使提取的模板相对于被检测部件存在任意角度的旋转,提出的模板匹配算法仍能准确地检测被识别的零部件。
The industry CT technology can accurately reconstruct the grey-level image of work piece internal structure,thus also can provide the possibility for non-destructively examining assembly defect （leak installing,mistake installing and multi-installing etc.）.This paper proposes a new template matching algorithm to realize the assembly defect detection.First,using the average grey-level vector of template to carry on the thick search,determines the candidate match set of points.Next,using the Zernike moment of template to carry on the accurate search,locates the target.The experimental result indicates that,even if the template has the free angle revolving opposite to the examined work piece,the proposed algorithm also can successfully locates the target.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第10期209-210,213,共3页
Computer Engineering and Applications
基金
国家部委十一五基础研究
重庆市自然科学基金(the Natural Science Foundation of Chongqing City of China under Grant No.CSTC2005BA2002)
关键词
图像重建
自动识别
平均灰度矢量
ZERNIKE矩
image reconstruction
automatical recognition
average grey-level vector
Zernike moment
