Binocular vision is an important branch of computer vision that processes images captured from two different cameras with different perspectives to obtain depth information of a scene. However, the stereo matching algorithm is complex and traditional platforms often struggle to meet real-time and accuracy requirements simultaneously. In this article, we implement a binocular vision system based on the idea of software-hardware co-design on the Zynq platform. According to the characteristics of the Zynq platform, the system's software and hardware functions are divided. The processing system (PS) is mainly responsible for flow control and binocular correction, while the programmable logic (PL) is responsible for parallel acceleration of the stereo matching algorithm. In the image acquisition part, we configure the format and output image timing using a designed camera acquisition module. In the stereo matching part, we design a semi-global stereo matching algorithm using Verilog language. Finally, we build a binocular vision system on the Zynq platform for testing. The experimental results show that the frame rate can reach 30fps when the input image resolution is 640×480, which satisfies the requirements of real-time and accuracy of the output disparity map.
In order to effectively solve the problem of real-time distance measurement of traffic signs in intelligent driving environment perception, a distance measurement method based on binocular vision is proposed. In order to solve the problem of real-time distance measurement, the paper proposes to build a correction mapping table, through which the correction coordinates corresponding to any distorted coordinates can be read out. The calibrated parameters are used to calculate the correction mapping table. The coordinates of left and right traffic signs can be obtained through pyramid template matching. Then the parallax is obtained and the distance is measured. The error rate of the measurement method is less than 2.33% within 20 meters to 60 meters. The time of one-time measurement is within 20ms in embedded environment.
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