Robust and reliable traffic surveillance system is an urgent need to improve traffic control and management. Vehicle flow detection appears to be an important part in surveillance system. The traffic flow shows the traffic state in fixed time interval and helps to manage and control especially when there's a traffic jam. In this project, we propose a traffic surveillance system for vehicle counting. The proposed algorithm is composed of five steps: background subtraction, blob detection, blob

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... alysis, blob tracking and vehicle counting. A vehicle is modeled as a rectangular patch and classified via blob analysis. By analyzing the blob of vehicles, the meaningful features are extracted. The experimental results show that the proposed system can provide real-time and useful information for traffic surveillance.