Object Detection and Ranging System Based on Binocular Vision

For the Census transform stereo matching algorithm is susceptible to noise leading to mis-matching, a stereo matching algorithm based on the improved Census transform is proposed, which improves the Census transform reference value selection and incorporates the image gradient information to form the initial cost. Train the lightweight network model NanoDet to quickly detect and obtain the object position, and combine the object disparity and camera parameters to obtain the distance of the object, and transplant the system to an embedded device for practicality verification. After analyzing and verifying the experimental data, it shows that the anti-noise capability of the improved algorithm is significantly improved, and the proposed method can quickly complete the detection and ranging tasks on embedded devices with high reliability and practicality.