An improved interframe differential target detection and tracking algorithm based on multi-region information fusion constraints
1.School of Mechanical Engineering, Shandong University of Technology, Zibo, Shandong 255049, China; 2. School of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo, Shandong 255049, China
Abstract： To solve the problem of frame difference method with rough target detail recognition, an improved target detection and tracking algorithm was proposed, and a detection method combining twotime region restriction algorithm and Kalman filtering algorithm was constructed. The dynamic region of interest (ROI) was obtained by the proposed grid partitioning algorithm, and the lane line region was identified only within the salience range of the road. According to the lane line area information and with the established road area mask as evaluation index of the frame difference method, the processing accuracy of the algorithm was improved. An extended Otsu algorithm was adopted to solve the problem of effectiveness of target extraction performance with frame difference method by adaptive dynamic threshold. With the detected centroid coordinates of target as observation quantity, the target trajectory was tracked and predicted through Kalman filter. Halcon vision software platform was used to verify the performance of the proposed algorithm. The results show that the average processing time of the proposed algorithm is 32.132 ms, which can meet the realtime requirements. The average accuracy of lane line detection is more than 95%. The proposed algorithm can quickly and accurately extract the lane area and identify the target position in the environment.
