A 3D shape measurement method for high-reflective surface based on accurate adaptive fringe projection

Fringe projection profilometry (FPP) is a popular three-dimensional (3D) shape measurement technique with advantages of high-precision and non-contact. However, measuring high-reflective surface is still a challenging task for conventional FPP because image saturation leads to absolute phase errors and reconstruction errors. In this paper, a new adaptive fringe projection (AFP) method is proposed. Compared with existing AFP methods, we simplify the experimental process and get more accurate coordinate mapping. First, we built the projection intensity model for each projector pixel rather than camera pixel. Then, a uniform gray pattern was projected and two images were captured under high and low exposures respectively to calculate the quantitative low projection intensity. In coordinate mapping, sub-pixel coordinates were mapped from camera image onto projector image. They were filtered with absolute phase to deal with resolution difference between camera and projector and get accurate coordinate correspondence. Finally, adaptive fringe patterns were generated. Besides, we proposed a novel quantitative criterion to evaluate the effectiveness of AFP methods called point cloud integrality (PCI), which is calculated based on the number of 3D points of high-reflective areas. The experiments demonstrate that the proposed method increases both the measurement accuracy and PCI compared with conventional FPP and some existing AFP methods.

Automated summary

A new adaptive fringe projection method is proposed in this paper, which simplifies the experimental process and obtains more accurate coordinate mapping to increase both the measurement accuracy and point cloud integrality.