基于机器视觉的公差检测系统算法研究与应用——自适应边缘检测与修正Hough变换

介绍了基于机器视觉的几何量和位置公差检测中常见的计算模型、图像处理和直线拟合一般算法，进一步介绍了一种自适应的边缘检测方法。着重分析了传统的Hough变换的优势和缺点，在此基础上提出了适应形位公差检测特点的修正Hough变换算法。自适应边缘检测方法被应用于检测实际工程的图像边缘，检测到的边缘区域在亚像素之内；修正的Hough变换算法也被运用于相应工程的直线拟合，与传统的Hough算法相比，结果表明其速度更快、精度更高，抗干扰能力更强，其拟合直线的极径精度可达到0．1个像素，极角精度可达0．01°。

Geometric measurement system on computer vision——auto-adaptable image edge detection and improved Hough transform algorithm

The algorithms of geometric measurement model,image processing and line edge fitting for computer vision are introduced in this paper.Moreover,auto-adaptable image edge detection method is advanced.This paper essentially analyzes the advantage of original Maximum Hough Transform(MHT) with weakness.Based on MHT,Improved Hough Transform(IHT) is put forward to adapt for geometric measurement.IHT is used to proceed line edge fitting in the actual engineering.The auto-adaptable image edge detection method is applied to detect image edge in real project,and the region of image edge detected is limited within 1 pixel.IHT is also applied to fit line edge.Comparing with MHT,the result of IHT indicates its speed quick,the accuracy high,and anti-jamming-quality strong,exactly shows that the accuracy of IHT fitted line is less than 0.1 pixel for polar distance and less than 0.01° for polar angle.