Multi-channel Digital Fringe Calibration for Structured Light Profilometers using Neural Networks

The performance of structured light profilometers is significantly hindered by the generation of distorted sinusoid fringe images, particularly, for multi-channel applications. In this paper we investigate the application of neural network fringe calibration for the multi-channel approach. We analytically review the nature of the major error sources associated with the multi-channel approach and propose a fringe calibration technique with emphasis on minimal photometric calibration. The performance of the calibration technique is gauged through both simulation and experimentation.