Study On The Key Techniques Of Image Tracking System On Armored Car

In the future local war of high technology, people on the armored vehicle must processabundant information in the moment of battling against the enemy target, so an automatic targettracking system is needed which hangs sensors, processor and display and so on together. Such asystem should extract the target from complicated and chaotic background of scatteringdisturbance quickly and reliably, thereby people on vehicle can react to the enemy target asquickly as possible. However, the working condition of armored vehicle is abominable andmultiplicate, the targets are diversified, and the tracking system is sensitive to the platform's vibration. All these things have caused great difficulty in developing image tracking system onarmored vehicle.This paper probes into the technical difficulties in the application of image tracking systemon armored vehicle, and studies on the target detection, recognition and tracking techniques onvehicle. It also investigates the realizing technology of image tracking system on vehicle, andaccomplishes the development task of corresponding project.The primaryresearch of this paper includes:①Setting up the tracking theory of image tracking system on armored vehicle. First, thepaper constructs the system's mathematical model and brings out the tracking equation according to the analysis of system task and tactics-technology index. Second, it divides the state of systemin order to solve the tracking equation, and constructs the basic function structure of systembased on the description of each working state. By analyzing the system's basic theory, this paperpoints out the system difficultyand our study emphasis.②Putting forward a real-time electronic image stabilizing algorithm (EIS) in allusion to thedisturbance to image sequence by vehicle vibration. First, it delves into the key technique of EIS—image registration, and presents an effective registration algorithm which is from coarse toprecise and form local to global. Second, it applies recursive Kalman filtering technique inmotion filtering of registration parameters and makes motion compensation for practical image.Finally, it takes advantage of mosaicking to reconstruct undefined regions to avoid theubiquitous information missing and image degradation. This algorithm has high precision as wellas high speed.③Bringing forward an intelligent decision method of image segmentation based on roughset theory to make the system automatically select segmentation algorithm in simple scenes.Firstly, it selects some representative segmentation algorithms to make up of an algorithm library,which is used to process kinds of sample images; secondly, it makes the decision informationtable utilizing diversified numerical features extracted from the sample images and the optimalsegmentation algorithm of each sample image according to segmentation quality evaluationcriterion; finally, it applies rough set theory on discretization and attribution reduction of...