条纹投射技术中的投影机非线性自校正方法研究进展

在条纹投射技术中,投影机光强非线性是影响测量精度的关键因素之一。投影机非线性会在条纹信号中引入高阶谐波,从而导致位相测量结果中出现波纹状误差。投影机非线性的自适应校正方法,也即自校正方法,可以从测量数据中直接估计投影机输入输出光强曲线或位相误差函数,从而避免了繁琐的前标定过程,并因此在应用中具备很强的适应性。文中拟对投影机非线性自校正算法的研究进展作一个系统性的概述。这些方法中,其一,是从采集的条纹图像中利用迭代拟合算法直接估计投影机的非线性曲线,并依据其校正位相误差;其二,是从单幅测量位相图中识别并移除由非线性引起的位相误差;其三,是利用两幅不同频率的测量位相图估计误差系数,并补偿其影响。实际测量结果表明:上述自校正方法,在无需标定数据条件下,可以有效地解决投影机非线性误差问题,有助于提高条纹投射技术的测量精度。

Progress in self-correcting methods of projector nonlinearity for fringe projection profilometry

In fringe projection profilometry, the luminance nonlinearity of the projector has been recognized as one of the most crucial factors decreasing the measurement accuracy. It induces the ripple-like artifacts on the measured phase map. The self-adaptive correcting algorithms, i.e., self-correcting algorithms, allow us to suppress the effect of the projector nonlinearity without a prior calibration for the projector intensities or phase errors. This paper introduces the research progress in the self-correcting algorithms. Among them, the first algorithm is to determine a nonlinear curve representing the projector nonlinearity, directly from the captured fringe patterns, thus correcting the phase errors using this curve. The second one is to recognize and remove the nonlinearity-induced errors, directly from a calculated phase map. With the last one, error function coefficients are estimated from a couple of phase maps having different frequencies. Measurement results demonstrate these self-correcting algorithms to be effective in suppressing influences of the projector nonlinearity in the absence of any calibration information.