Tracking Algorithm, Based On Infrared Video Sequence

Moving target detection, recognition and tracking is the key point of the Image Process and Pattern Recognition. Its applications are related to military defense, astronomical observation, security testing, industrial production, Medical and health. To process the moving target in the video, the study is essentially of the image sequence.In this paper, the structure and basic method of image tracking system are reviewed and analyzed. On this basis, the image preprocessing algorithms based on gray-level correction and spatial filtering are studied, and lay a good foundation of multi-target tracking which is based on infrared video sequence. The image segmentation technology such as maximum variance between clusters and the image matching technology is studied. This subject adopts the new targets detection algorithm which is combined by maximum variance between clusters and image difference method to detect the targets . After analyzing the tracking algorithms of boundary tracking, peak tracking and centroid tracking, the improved centroid tracking algorithm is chosen. Then the method of comparing candidate centroids with the pixels of targets in the motion compensation prediction error information (we call it MCPR for short afterwards) images is put forward. Finally, the targets detection algorithm which is combined by maximum variance between clusters and image difference method, and the centroid tracking algorithm are simulated and analyzed for infrared video sequence, and realizes the multi-target tracking based on infrared video sequence , which obtains a favorable effect.The subject puts forward the targets detection algorithm which is combined by maximum variance between clusters and image difference method, and the method of comparing candidate centroids with the pixels in the same coordinates in MCPR image innovatively, which achieves fast and efficient targets detection and judgment of real centroid.