An Optimizing Diffusion Kernel-Based Binary Encoding Strategy With Genetic Algorithm for Fringe Projection Profilometry

Abstract

The binary encoding fringe projection profilometry has the potential of achieving high-speed 3-D measurement. Error diffusion is one of the most widely investigated binary encoding techniques. However, the existing error diffusion usually utilizes the same diffusion kernel to encode sinusoidal (S) fringe patterns without considering the fringe pitch-widths, leading to inevitable measurement error due to the demodulated phase error. In this article, a fringe binary encoding strategy based on genetic algorithm is proposed to reduce the phase error recovered by the temporal phase unwrapping (TPU) method. We design an optimization equation that combines phase error and intensity error to calculate the encoding error, which ensures that the optimized diffusion kernel is robust to defocusing changes. Both simulation and experiments have proved the effectiveness and accurateness of the proposed method. Comparative experiments indicate that the extracted phase error is greatly reduced for two types of extensively adopted TPU methods at different defocusing levels. Especially for multi wavelength method, the phase error can be reduced by up to 68%.