计算机科学
投影机
非线性系统
离群值
稳健性(进化)
校准
人工智能
算法
轮廓仪
计算机视觉
数学
物理
生物化学
化学
统计
量子力学
表面粗糙度
基因
作者
Zhongyi Xia,Peng Hou,Tao Song,Qian Li
标识
DOI:10.1016/j.optlastec.2023.109745
摘要
In phase-shifting profilometry, the nonlinearity of the projector is the main error source which undermines the 3D reconstruct accuracy. Most calibration algorithms mainly focus on calibrating the nonlinear responses and compensating for the related errors. However, it requires a tedious pre-calibration process. In this paper, a phase registration algorithm based on Gray code guidance is proposed, Hough transform and majority voting are performed to accurately locate the boundary of Gray code, two strategies are introduced to select correct phase matching pairs. In addition, to eliminate mismatched points and improve the accuracy of the fitting, outlier detection technology is used to iteratively fit phase matching pairs. Finally, the error is compensated point by point using the fitting curve. Experimental and simulation results demonstrate the effectiveness of the proposed method. It has the advantages of simple deployment, no photometric pre-calibration, high accuracy, strong robustness, and can handle the projector's nonlinearity that changes with time.
科研通智能强力驱动
Strongly Powered by AbleSci AI