摘要
研究零件缺陷检测问题。针对要求机械零件精密度高,传统的图像检测或者肉眼检测很难保证精密零件的细微缺陷被准确检测出来。提出计算机视觉图像的缺陷零件检测方法。采取了去除小成分的方法去除图像中的噪声和一些干扰测量的部分;选取最大类间方差法作为此检测系统的阈值分割方法。采用像素级和亚像素级边缘检测,克服传统方法的缺陷,实现精密零件缺陷的完整检测。实验结果证明,方案切实可行,提高了测试精度,为图像检测提供了可靠的方法。
Study the part defects detection.Today's mechanical parts are becoming more and more precise,and it is difficult for traditional image detection or naked eye detection to ensure that the parts was accurate detected.Based on computer vision image,this paper put forward a defective parts detection method.The method of removing minor components was adopted to eliminate the noise of the image and some interference measurement part.The Otsu method was used foe the segmenting threshold.Pixel level and subpixel level edge detection were used to complete the precise components defects detection.Experiments show that this scheme is feasible,and can achieve high accuracy and shorter testing time.
出处
《计算机仿真》
CSCD
北大核心
2012年第3期273-276,共4页
Computer Simulation
关键词
缺陷检测
去除噪声
阈值分割
Defects detection
Eliminate the noise
Threshold segmentation