Micrometer-level 3D measurement techniques in complex scenes based on stripe-structured light and photometric stereo.

Compared with existing depth cameras, such as RGB-D, RealSense and Kinect, stripe-based structured light (SL) has the potential for micrometer-level 3D measurement; this can be attributed to its higher coding capacity. While surface texture, high-reflective region, and occlusion remain some of the main sources leading to degraded reconstruction quality in complex objects, methods that are only based on SL cannot completely solve such problems in complex object reconstruction. In this paper, we developed an advanced fusion strategy for the reconstruction of complex objects in micrometer-level 3D measurement. This includes solving the above-mentioned inherent problems of a stripe-based SL system with the aid of photometric stereo (PS). Firstly, to improve the robustness of decoding and eliminate the effects of noise and occlusion on stripe detection, a novel scene-adaptive decoding algorithm based on a binary tree was proposed. Further, a robust and practical calibration method for area light sources in the PS system, which utilizes the absolute depth information from SL system, was introduced. A piecewise integration algorithm, which is based on a subregion divided by Gray code, was proposed by combining the depth values from SL with the normal information from PS. Remarkably, this method eliminates the effects of surface texture and high-reflective region on the reconstruction quality and improves the resolution to camera-level resolution. In experimental parts, a regular cylinder was reconstructed to demonstrate micrometer-level measurement accuracy and resolution enhancement by the proposed method. Then, improvement of the reconstruction accuracy for objects with surface texture was validated with a regular pyramid that had textures on it and a white paper with characters printed on it. Lastly, a complex object containing multiple phenomena was reconstructed with the newly proposed method to show its effectiveness for micrometer-level 3D measurement in complex objects. Evaluation of our proposed method shows the improvement of the proposed method on the existing methods being used for micrometer-level 3D measurement in complex objects.