Infrared Small Target Detection and Tracking Method Suitable for Different Scenes

An infrared small target detection and tracking method suitable for different scenes is proposed. For a given infrared image sequence, 1) firstly, the complexity of the scene is judged according to the number of Harris corners; 2) for the image sequence containing simple scenes, the method of local adaptive threshold segmentation and track association is used to complete the detection and tracking of multi-target; 3) for the image sequence containing complex scenes, SSD detector is used to detect the initial target, after the target is detected, SiamRPN++ tracker is started to track the target. The tracking result is judged in the tracking process. When the target is lost or wrong, the SSD detector is restarted immediately to capture the correct target position and fed it into the tracker to complete the reinitialization and correction. In the tracking process, different targeted strategies are adopted to deal with different situations, such as the target entering and leaving the field of view, the sudden change of the moving state, false alarm interference and so on, ensuring that the detection and tracking of the whole image sequence is completed efficiently and stably. The proposed method which provides solutions for different scenes can successfully realize the continuous and accurate positioning of multiple infrared targets in different scenes, improving the ability of the infrared detection system to solve practical problems. Especially for the complex scene, the neural network based intelligent detector and tracker complement each other to improve the detection and tracking efficiency of infrared dim small targets, and have strong robustness and generalization performance.