Detecting and Numerating Vehicles from CCTV Traffic CameraMovies Using a Support Vector Machine

Nowadays closed circuit televisions (CCTV) have been highly developed andhave been utilized in most of road intersections and places with heavycongestion. CCTVs are very useful for automation of traffic control by vehicledetection and computing the number of vehicles automatically from CCTVs;controlling urban roads, as well as accident management with high accuracy andspeed would be possible. In this paper, a different procedure for detecting andnumerating vehicles was proposed from CCTV traffic camera movies. In thisregard, at first a region of roads was detected using the frames of a short part ofCCTV movies. Then in order to gather the training data in the detected region,some features were selected according to their ability in clarifying vehicles.Afterwards, a support vector machine (SVM) and an artificial neural network(ANN) were proposed for detecting vehicles. Finally, the number of vehicleswere computed by binary results from detected vehicles. Comparing the resultsof the proposed ANN-based method with the proposed SVM one reveals that theproposed SVM-based method has a better performance in computing the numberof vehicles in cameras that have a long distant from vehicles.

Detecting and Numerating Vehicles from CCTV Traffic CameraMovies Using a Support Vector Machine Keywords:

Vehicle detection , Road region , Support Vector Machine , Artificial NeuralNetwork , CCTV camera movies