基于自适应条纹投影的高反光物体三维面形测量

结构光投影方法在三维形貌测量中应用广泛，但是由于被测物体表面反射率变化范围较大，过度曝光会导致相位信息无法获取。而传统的高动态范围扫描技术步骤复杂，耗时较长。文中提出一种自适应条纹投影技术，向待测物体表面投射较高灰度级的条纹图，判断并标记过度曝光点。降低投射强度后通过非线性最小二乘法拟合来确定每个饱和像素点最适合的最大输入灰度，用重新生成的自适应条纹图来采集图像并进行相位计算和三维形貌恢复。通过实验验证，该方法可以对物体表面的高反光区域进行有效测量，避免过度饱和，仿真误差在0.02 mm范围内，实测误差约为0.14 mm，实际实验对过曝点的补偿率可达到99%。

Three-dimensional shape measurement of high reflective objects based on adaptive fringe-pattern projection

Structured light fringe projection methods have been commonly used for three-dimensional (3D) shape measurements. However, for objects with large surface reflectivity range, saturation of the captured fringe pattern images leads to the phase information unavailable. The traditional high dynamic range scanning (HDRS) technique is complicated and time-consuming. An adaptive fringe-pattern projection method is proposed. Firstly, a sequence of phase-shifted fringe patterns with high gray level is projected onto surface of the measured object, which is used to predict and mark the overexposed points. Subsequently, the maximum input gray level (MIGL) of each saturated pixels is determined by the nonlinear least squares (NLS) fitting method based on the captured images with middle exposure level. Finally, the adapted fringe patterns are projected for phase calculation and 3D shape recovery. The experimental results demonstrate that the proposed method effectively achieved 3D shape measurement of object by avoiding image saturation in high-reflective surface regions. The simulation error of the proposed method is within the range of 0.02 mm. Compared with this, the actual measurement error is 0.14 mm, and the compensation rate for the over-exposure points can reach 99% in the actual experiment.