High dynamic range three-dimensional shape reconstruction via an auto-exposure-based structured light technique

High dynamic range object has large surface reflectivity variations, which easily produces saturated and low-contrast regions in the captured images, further resulting in large calculation errors of gray value or phase value, then seriously affecting the reconstruction accuracy. An auto-exposure-based structured light technique is proposed. In this method, the relationship between noise-induced phase error and intensity modulation is first analyzed. It is demonstrated that once the intensity modulation of a pixel is larger than a threshold, its phase error can be considered acceptable. Then, the surface reflectivity of the measured target is estimated by projecting a series of uniform gray-level patterns and classified into several groups. The exposure time for each group is automatically determined after establishing its mathematical model based on the modulation threshold. Phase-shifted images are then captured at the computed exposure times, and a set of composite phase-shifted images is acquired by extracting the brightest unsaturated pixels in the raw fringe images. The experiments show that the proposed method can automatically calculate the exposure times and capture the fringe images without human intervention. In addition, it can well tackle saturated and dark areas of the measured target and the reconstructed three-dimensional shape is complete and accurate.