Stereo vision using Gabor wavelets

Abstract

The analysis of video images in stereo can extend machine vision to interpret the 3-D structure of a scene. Applications of stereo vision include robotics, industrial automation, autonomous land rovers and automated cartography. The simplest stereo paradigm, binocular stereo vision, provides man and many animals the capability to see the depth from two images without ambiguity. Thus, it is interesting to study the biological solution to stereopsis. In this paper, a biologically motivated model of stereopsis based on a coarse-to-fine matching algorithm using multiband Gabor wavelets is presented. This approach generates a dense disparity map by phase difference computation between stereo image pairs without complex feature extraction. Results of the algorithm for both synthetic and natural stereo images are presented.<>