A Robust Surface Coding Method for Optically Challenging Objects Using Structured Light

Though the structured light measurement system has been successfully applied to the profile measurement of diffuse objects, it is still a challenge to measure shiny objects due to the mix of both specular and diffuse reflections. To this end, we propose a robust encoding and decoding method in this paper. First, the monochromatic stripe patterns are utilized to eliminate the effect of texture and color of objects. Second, an intensity mask, dynamically adjusting the intensity of a projected pattern, is applied to avoid overexposure without any pre-knowledge of the workpiece. Thus, it is more flexible and efficient, compared with the existing methods. Third, to solve the internal reflection of the shiny part, an extrapolation model, combined with the intensity mask, is developed to detect the stripe edge for pattern decoding, resulting in accurate and robust 3D reconstruction. Compared with traditional polarization based methods, it does not need to readjust for a new part. The experimental results show that the proposed method is capable of measuring various parts without surface pretreatment. Note to Practitioners-In the manufacturing industry, there is a demand to measure workpiece for quality control. A Coordinate Measurement Machine (CMM) is usually used. However, its pointwise measurement makes the inspection time consuming and cannot do 100% inspection for all the parts. Vision-based 3D-reconstruction method could measure the parts quickly. But the method is weak against optically challenging objects. To this end, this paper proposed a robust surface coding method to measure the optically challenging object via a vision-based method.