Optimization of Adaptive Lighting Technology Based on Varying-Frequency Sinusoidal Grating Projection

In order to enhance the image quality of multi-reflective 3D scenes during machine vision analysis, an active self-adaptive illumination system to solve the overexposure and underexposure problems is introduced. Based on projector-camera system, adaptive illumination was achieved by modulating the projection brightness at each pixel to be proportional to the pixel brightness of the target scenes, which should firstly establish the accurate pixel correspondence between the projector and camera. In this paper, the performance of adaptive illumination is improved by optimizing the correspondence stage compared with previous research. Different grating patterns with different frequency components are projected and compared to acquire the most effective correspondence, which improves the accuracy of corresponding depth map and the experiment results can achieve higher lighting accuracy reducing the number of iterations as well as the computing time. The image quality indexes, image contrast and number of saturated or dark pixels, are combined to analyze and judge the optimized lighting result. The results demonstrate that the developed technology in this research can achieve a rate of 20 frames per second by using a standard commercial CCD (charge coupled device) camera, where it can run in real time and becomes a viable solution for the industry.