SPEEDZO: Vehicle speed detection using Video Processing

In the modern world, reckless driving has been a major contributing factor in many road accidents. Various researches and studies have already been done on speed detection and published on the Internet. Proposed approach roughly involves three steps: background removal, feature extraction, and vehicle tracking. Our model will help in detecting the over speeding of vehicles on the highways by mainly presenting an algorithm for estimating vehicles speed based on target detection in video surveillance. The proposed algorithm uses various techniques such as Kalman filtering, contour tracing, centroid tracking, zth image, background subtraction, vehicle segmentation, computing centroid, speed detection, and calculation. This study describes how to find a vehicle, track its speed using video processing, and mathematical technology for detecting, tracking, and calculating vehicle speed. Our approach towards this problem is mainly done through a video input to make the system work to analyze the vehicle traveling speed using computer visioning to exploit and manipulate data from videos to extract and estimate useful data. The algorithm can be applied to various types of video surveillance systems and can be used for real-time monitoring of traffic violations.