基于U-Net网络的结构光三维测量术

U-Net-based Structured Light Three-dimensional Measurement Technology

结构光条纹投影是广泛应用的一种三维测量技术。虽然该技术经过几十年的研究和发展,但如何从单幅图像中快速获取物体三维形貌仍然是没有得到很好解决的难题之一。近几年,深度学习方法广泛应用于计算机视觉和图像处理领域。提出一种基于U-Net网络的结构光三维测量方法。该方法直接从单个变形条纹图中获取物体表面的深度信息,实现三维形貌的快速测量。仿真和实际实验数据证明了所提方法的有效性。由于仅从一幅变形条纹中计算得到三维数据,所提方法可应用于动态物体三维面形的测量。

Structured light fringe projection is widely used in three-dimensional(3D)shape measurement technologies.However,even after decades of related research and development,restoring the 3D shape of objects using a single fringe pattern remains a challenge.In recent years,deep learning methods have been used increasingly in computer vision and image processing tasks.Thus,this paper proposes a structured light 3D measurement method based on the U-Net network.The proposed method obtains the depth information of the target object’s surface directly from a single deformed fringe pattern to realize high-speed 3D shape measurement.Simulated and experimental data prove the effectiveness of the proposed method.With the proposed method,3D data can be calculated from a single deformed fringe pattern;thus,it can be applied to the 3D shape measurement of dynamic objects.