Design of Target Detection and Ranging System Based on YOLOv5 and Parallax Computing Algorithm
Visual object detection and ranging is a technology that uses computer vision technology to detect and distance target objects in images or videos.This technology plays an important role in the field of industrial automation.Based on the YOLOv5 algorithm,the parallax computing algorithm perspective transformation was used to estimate the parallax value of each pixel during target detection,and the trained parallax neural network model was used to replace the traditional triangulation principle to achieve target detection and ranging.In order to speed up the calculation,the latest parallel computing framework OpenCL was used to give full play to the parallel computing capability of the computing equipment,operating efficiency was increased by 43％,the target detection was more accurate and faster,and the ranging accuracy was improved.Firstly,the binocular camera was called to detect the target object,and the corresponding boundary frame and confidence were obtained.Then,the actual distance of the target object was calculated by using the camera's angle difference and the stereo matching function of binocular vision.The experiment was carried out outdoors.The results show that the system can accurately detect the outdoor target obstacles and realize the target distance measurement,and the distance measurement error is less than 4％in the range of 0.5～1.5 m,which provides a technical reference for the inspection robot to automatically avoid obstacles.
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