Robust Stereo Matching Algorithm Based on Spatial Constraints under Rectification.

Medical intelligent navigation systems have attracted increasing attention, and binocular optical tracking systems being an important component to ensure accurate tracking navigation. However, ghost markers may appear when there are multiple markers on the same plane, which can result in tracking errors and significantly impact the surgical process. In this paper, we propose a robust stereo matching algorithm based on spatial constraints under rectification. The algorithm is verified using a binocular vision system based on Xilinx Zynq-7020 platform of field-programmable gate array (FPGA), which meets the requirement of fast, real-time tracking of multiple instruments. The used matching algorithm has a tracking processing time of only 107 under four surgical instruments, which is 82.46% higher than the epipolar geometry method. Furthermore, compared with the traditional sequential matching method, this method improves the tracking failure rate by 6.46% for tracking four instruments, effectively avoiding false matching caused by the appearance of ghost markers.