A Rectification Hardware Architecture for an Adaptive Multiple-Baseline Stereo Vision System

Abstract

In this paper, we propose a new rectification hardware architecture that is suitable for an adaptive multiple-baseline stereo vision system. The adaptive multiple-baseline stereo vision system can obtain precise distance information compared with the fixed-baseline stereo vision system. To reduce the computation overhead of the stereo matching, the rectification is an essential step in the stereo vision system. However, the conventional rectification hardware architectures are designed for the fixed-baseline stereo vision system. Also, previously proposed the lookup table (LUT) based rectification hardware architectures are not suitable for the adaptive multiple-baseline stereo vision system. This is because these require large memory resources as the number of baseline increases. The experimental results show that the proposed hardware architecture does not need memory resources and also only few additional hardware resources are required as the number of the baseline increases as compared with the LUT-based rectification hardware.