Abstract: In order to achieve target tracking in static background, a DTC-based perceptual Hash generation algorithm is used to extract the target-aware Hash summary, and the Hamming distance is compared to achieve template matching. Aiming at the problem of insufficient tracking efficiency, a range and azimuth fusion prediction strategy is proposed, in which the range predicts the range of the predicted target and narrows the template search area. The azimuth prediction finds a faster and shorter search route based on the range prediction. The tracked coordinate elements are simplified into a single azimuth feature, the four prediction models are used to predict the target orientation, a template matching termination condition is mined, the window traversal is stopped at an appropriate depth. The experimental results show that the range prediction improves the tracking efficiency significantly. When the prediction range is reduced by n times, the algorithm efficiency is improved by about n² times, and the azimuth prediction can improve the efficiency by about 16% based on the range prediction.

Key words: perceptual Hash, template matching, range prediction, azimuth prediction, target tracking