Depth perception from a single camera and multiple light sources

Abstract

3D Vision has always been a subject of research for many decades. The use of images results in the loss of the 3rd dimension. Many techniques have been developed over the years that aim in acquiring depth from images. Among the most widespread are stereo vision, fringe projection, laser scanning or combinations of them, all of which have shown high quality results but unsuitable for some classes of applications. For example, laser scanning rangefinders are not low-cost system. Hence, there is a need to develop a low cost, high speed, high resolution system for 3D vision. In this thesis a novel approach is presented to estimate depth using a single camera combined with two spectrally distinct light sources for road surface measurements. The light sources consist of two sets of LED arrays. Depth information can be extracted, by processing the different reflections in the image from the two light sources. The basic information of depth estimation lies in their blue to red ratio, which with appropriate calibration is correlated to depth. The methodology was first developed in MATLAB and then was implemented on FPGA. The system is real time and fully optimized to have the minimum hardware resources and high frequency of operation for high resolution images.