3-D Shape Measurement of Complex Objects by Combining Color-Coded Fringe and Neural Networks

作     者：秦大辉 李中伟 王从军 史玉升 

作者机构：State Key Laboratory of Material Processing and Die and Mould Technology Huazhong University of Science and Technology 

出 版 物：《Tsinghua Science and Technology》 (清华大学学报（自然科学版（英文版）)

年 卷 期：2009年第14卷第S1期

页      面：66-70页

核心收录：

学科分类：08[工学] 0802[工学-机械工程] 080201[工学-机械制造及其自动化] 

基　　金：Supported by the Eleventh Five-Year Pre-Research Project of China 

主　　题：three dimensional (3-D) shape measurement color-coded fringe neural networks correspondence problem 

摘      要：A new approach for three dimensional (3-D) shape measurement was proposed based on colorcoded fringe and neural networks. By applying the phase-shift technique to fringe projection, point clouds were generated with high spatial resolution and limited accuracy. The picture element correspondence problem was solved by using projected color-coded fringes with different orientations. Once the high accurate corresponding points were decided, high precision dense 3-D points cloud was calculated by the well trained net. High spatial resolution can be obtained by the phase-shift technique and high accuracy 3-D object point coordinates are achieved by the well trained net, which is not dependent on the camera model and will work for any type of camera. Some experiments verify the performance of this method.