Line extraction from images of industrial components based on CAD
张春森 Zhang Chun-sen, 胡平波 Hu Ping-bo · Optics and Precision Engineering · 2011
For feature extraction from image measurements and reconstruction from industrial component images,a mathematical model guided by Computer Aided Design(CAD) data is put forward to detect image lines with high accuracy.Firstly,using CAD data,the line initial values are obtained by projecting object line features through the conversion of 3D CAD coordinate and images.Then a sequence of edge points are extracted by adaptive least squares template matching(LSTM) and leads to image line equations from these points based on the principle of least squares fitting.Finally the contours of industrial components are obtained accurately by solving the intersections of image intersecting lines.By using the algorithm on real images of industrial components,we perform a line feature extraction experiment with an average standard deviation of 0.232 mm between the rebuilt line and the actual line length.This proves that the algorithm has high automation extraction and strong stability,and can be used to the image measurement and reconstruction of industrial components with high accuracy.