A 3D Measurement Method Based on Coded Image

Abstract

The binocular stereo vision system is often used to reconstruct 3D point clouds of an object. However, it is challenging to find effective matching points in two object images with similar color or less texture. This will lead to mismatching by using the stereo matching algorithm to calculate the disparity map. In this context, the object can’t be reconstructed precisely. As a countermeasure, this study proposes to combine the Gray code fringe projection with the binocular camera as well as to generate denser point clouds by projecting an active light source to increase the texture of the object, which greatly reduces the reconstruction error caused by the lack of texture. Due to the limitation of the camera viewing angle, a one-perspective binocular camera can only reconstruct the 2.5D model of an object. To obtain the 3D model of an object, point clouds obtained from multiple-view images are processed by coarse registration using the coarse SAC-IA algorithm and fine registration using the ICP algorithm, which is followed by voxel filtering fusion of the point cloud. To improve the reconstruction quality, a polarizer is mounted in front of the cameras to filter out the redundant reflected light. Eventually, the 3D model and the dimension of a vase are obtained after calibration.