计算机应用 ›› 2010, Vol. 30 ›› Issue (07): 1841-1843.

• 图形图像处理 • 上一篇    下一篇

基于机器视觉的弧形件检测算法

师雪超1,孙振忠2,卢盛林2,杨玉梅3   

  1. 1. 华南理工大学;东莞理工学院
    2. 东莞理工学院
    3. 东莞市奥普特自动化有限公司
  • 收稿日期:2009-12-10 修回日期:2010-02-27 发布日期:2010-07-01 出版日期:2010-07-01
  • 通讯作者: 师雪超
  • 基金资助:
    科技型中小企业技术创新基金项目;东莞市科技计划

Inspection algorithm of arc-parts based on machine vision

  • Received:2009-12-10 Revised:2010-02-27 Online:2010-07-01 Published:2010-07-01

摘要: 为快速准确地对弧形零件特征参数进行检测,提出了一种基于机器视觉技术检测弧形件的各种特征参数的方法。该方法先采用Canny算子检测图像边缘,然后用三次样条插值方法对图像边缘进行插值并计算其亚像素坐标,最后采用基于切线方向的方法计算曲率值。对离散曲率数据进行处理,计算其均值和方差以及弧形件的弧长、夹角、面积等特征量。实验结果证明:该算法不仅精度高、速度快,而且稳定性好,能满足弧形零件特征参数的检测要求。

关键词: 机器视觉, 图像检测, 弧形件, 亚像素坐标, 离散曲率

Abstract: In order to achieve fast and accurate inspection on the feature parameters of the arcshaped piece, the paper presented a method that inspected feature parameters of the arc-shaped piece based on machine vision. First, the image edge was extracted by Canny operator and subpixel coordinate was computed by a cubic spline interpolation algorithm. Then, discrete curvature was computed by discrete curvature computing method based on tangent direction. The discrete curvature data were arranged; the mean and variance, as well as the arc-length, surface and angle of curved pieces were calculated. The experimental results indicate that the proposed method is of not only highprecision, high-speed but also good-stability, and can satisfy inspection requirement of arc-parts feature parameters.

Key words: machine vision, Image inspection, Arc-Parts, Sub-pixel coordinate, Discrete curvature