Based On The Particle Filter, Vehicle Tracking System And Its Implementation

Intelligent Transportation System (ITS) is the development trend of future traffic. The real-time and accuracy of information which ITS provided has brought a great convenience for people'lives and production. Image processing and computer vision technology are used to detect traffic conditions and gather information, which is an important research of intelligent transportation system. Vehicle tracking is one of the most key parts in it.In this paper, the movement vehicles in intelligent transport system are used as research objects. The difficult issues including vehicle tracking technology, particle filtering theory and its improved algorithms, design and implementation of information system are studied to develop a vehicle tracking system.In the aspect of vehicle tracking, the basic methods of vehicle tracking based on feature, region, active contour, model and the commonly used algorithm including kalman filter, particle filter algorithm are analyzed. The research is focus on principle and implementation steps of particle filter algorithm. Through analysis and comparison, the actual effect of these tracking algorithms is not very good. Therefore, basic particle filter tracking algorithm has been improved and a new vehicle tracking algorithm based on improved particle filter is proposed, then programming to realize. Experiments show that this algorithm basically meets the requirements of system on the actual fast road and has high practicability.In the aspect of the design and implementation of information system, the Visual C++6.0 and Open CV are used to develop vehicle information management system based on Access database. The programming methods of ADO access database are used to achieve the several functions of vehicle information, including data storage automatic, adding, deleting records and fuzzy querying according multiple requirements.