Stereo vision and fourier transform profilometry for 3D measurement

Abstract

A three-dimensional data measurement method combining stereo vision and Fourier transform profilometry(FTP) is proposed in this paper. Stereo vision is simple and fast but it is prone to mismatch in smooth areas. FTP has high accuracy over smooth areas but it can only measure a limited height gradient. Depth information of high quality is obtained by combining these two techniques. Firstly, the system was constructed with four CMOS sensor cameras and a projector. Four cameras’ position were adjusted to capture pictures of scene, and thus four depth maps were obtained from disparity. The rough depth map of the central camera field was obtained using image transform and image mosaic. Secondly, the rough depth map was segmented into parts with similar depth by Flood Fill algorithm. A mask was constructed based on each part to choose the proper areas of stripe image for FTP. Modulation analysis was used to get unwrapped phase from the distorted strip pattern caused by the object height. By merging the initial depth map with the depth map of FTP, the final depth map of high quality was obtained.