An accurate and cost-effective stereo matching algorithm and processor for real-time embedded multimedia systems

Stereo matching is a vision technique for finding three-dimensional (3D) distance information in various multimedia applications by calculating pixel disparities between the matching points of a stereo image pair captured from a stereo camera. The most important considerations in stereo matching are highly accurate results and real-time performance. Thus, this paper proposes an accurate stereo matching algorithm that uses both a census transform algorithm and the sum of absolute differences algorithm in a complementary manner and its real-time hardware architecture. In addition, the proposed algorithm uses a vertical census transform with cost aggregation (VCTCA) to reduce hardware costs while maintaining high matching accuracy. We model the proposed algorithm using C language and verify it in several environments. Using a hardware description language, we implement the proposed hardware architecture and verify it on a field-programmable gate array-based platform to confirm the cost and performance of the hardware. The experimental results show that the proposed algorithm using the VCTCA produces accurate 3D distance information in real environments and reduces the hardware complexity. Thus, the algorithm and its hardware architecture are suitable for real-time embedded multimedia systems.