基于双目视觉的林间目标测距系统研究.

Aiming at the problems of slow image acquisition and processing speed, large CPU load and low image resolution in traditional binocular vision-based distance measurement of trees and obstacles, a forest target ranging system based on binocular vision is designed to realize the rapid measurement of the distance of forest targets such as trees and obstacles. The binocular camera and FPGA (Field Programmable Gate Array) are used as the image acquisition and processing platform of the system, and the gigabit Ethernet is used to transmit the image to the PC. Then, MATLAB is used to complete the binocular calibration of the system, so as to obtain the internal and external parameters of the binocular camera. Finally, based on VS2022 platform, stereo matching is performed through SGBM (Semi-Global Block Matching) algorithm and BM (Block Matching) algorithm to obtain disparity map and depth map, so that the current distance between trees and obstacles can be obtained through the 3D coordinate information of key points of trees and obstacles. The results show that the relative error of tree and obstacle distance measurement results of SGBM and BM algorithms is less than 2% in the range of 1. 4 m, and the processing speed of the two algorithms for frame is 130 ms and 119 ms, respectively. The results show that the binocular visual ranging system can realize the rapid processing of image data, and it can complete the ranging of forest targets such as trees and obstacles more accurately, providing a reference for the application of computer vision technology in forest resource investigation. [ABSTRACT FROM AUTHOR]