Zhang Wei, Zhu Jiongguang, Han Yu, Zhang Manru, Li Jiangbo
Department of Computer Technology and Science, Anhui University of Finance and Economics, Bengbu 233030, China.
College of Intelligent Manufacturing, Foshan Polytechnic, Foshan 528137, China.
Sensors (Basel). 2024 Jun 21;24(13):4037. doi: 10.3390/s24134037.
By applying a high projection rate, the binary defocusing technique can dramatically increase 3D imaging speed. However, existing methods are sensitive to the varied defocusing degree, and have limited depth of field (DoF). To this end, a time-domain Gaussian fitting method is proposed in this paper. The concept of a time-domain Gaussian curve is firstly put forward, and the procedure of determining projector coordinates with a time-domain Gaussian curve is illustrated in detail. The neural network technique is applied to rapidly compute peak positions of time-domain Gaussian curves. Relying on the computing power of the neural network, the proposed method can reduce the computing time greatly. The binary defocusing technique can be combined with the neural network, and fast 3D profilometry with a large depth of field is achieved. Moreover, because the time-domain Gaussian curve is extracted from individual image pixel, it will not deform according to a complex surface, so the proposed method is also suitable for measuring a complex surface. It is demonstrated by the experiment results that our proposed method can extends the system DoF by five times, and both the data acquisition time and computing time can be reduced to less than 35 ms.
通过应用高投影速率，二元散焦技术可以显著提高三维成像速度。然而，现有方法对变化的散焦程度敏感，并且景深（DoF）有限。为此，本文提出了一种时域高斯拟合方法。首先提出了时域高斯曲线的概念，并详细说明了用时域高斯曲线确定投影仪坐标的过程。应用神经网络技术快速计算时域高斯曲线的峰值位置。依靠神经网络的计算能力，该方法可以大大减少计算时间。二元散焦技术可以与神经网络相结合，实现具有大景深的快速三维轮廓测量。此外，由于时域高斯曲线是从单个图像像素中提取的，它不会根据复杂表面变形，因此该方法也适用于测量复杂表面。实验结果表明，我们提出的方法可以将系统景深扩展五倍，并且数据采集时间和计算时间都可以减少到小于35毫秒。
