Binocular visual dimension measurement method for rectangular workpiece with a precise stereoscopic matching algorithm

Binocular vision measurement benefits from high prediction robustness and low structural complexity. However, there are still significant flaws in its accuracy. In this paper, binocular vision measurement of a rectangular workpiece is investigated. A new precise measurement method based on binocular vision is designed to achieve precise measurement of rectangular workpiece dimensions. Firstly, an algorithm for workpiece location based on Zernike moments and corner matching is proposed and employed to precisely locate the workpiece and extract the sub-pixel coordinates of discrete points on an image's edge. Then, a novel stereoscopic matching algorithm combined with epipolar-geometry and cross-ratio invariance (CMEC) is proposed to improve the accuracy of binocular vision stereoscopic matching. Finally, a projection plane is introduced after the 3D reconstruction of discrete points in the workpiece contours by fitting the plane with least squares. The projection plane limits the coordinate fluctuations of discrete points. Furthermore, the data screening is used to further improve the accuracy of size calculation. The experimental results of the standard checkerboard and actual workpiece show that CMEC's matching accuracy reached 99%, and the proposed method's measurement accuracy reached 0.018 mm. This work presents a novel algorithm for stereoscopic matching in binocular vision and machine vision measurement.