Efficient 3D measurement of a HDR surface based on adaptive fringe projection

3D measurement methods of a high-dynamic-range (HDR) surface based on adaptive fringe projection have aroused extensive research interest. They tend to pixel-wise adjust the fringe projection intensity to ensure full-field phase quality in light or dark regions, which has two problems: (1) traditional image intensity-based temporal phase unwrapping (TPU) is susceptible to noise in dark regions, and (2) it is time-consuming to project orthogonal fringe patterns for coordinate mapping and 3D reconstruction. Aiming to address these issues, we present an efficient adaptive fringe projection method where misaligned Gray code patterns are adopted to remove the phase error induced by low-frequency fringe patterns. Compared with traditional image intensity-based TPU, misaligned Gray-code-based TPU provides a better noise-suppression effect in dark regions, as Gray codes are generally better preserved than image intensity. Moreover, the images captured in the coordinate mapping process are shared for optimal projection intensity calculation and 3D reconstruction to reduce the number of total projection patterns, thus improving measurement efficiency. Extensive contrast experiments are conducted to demonstrate that the proposed method retrieves the 3D shapes of micro-scale HDR surfaces with high accuracy and a minimum number of projection patterns on the premise of high measurement integrity.