Neural-vision based approach for real-time roadtraffic applications

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Abstract
The authors describe a novel neural network and edge based image processing approach for road traffic analysis. An edge detection technique to detect vehicles is used, while a back propagation neural network is used to track and count vehicles. The neural network is trained for various road traffic conditions and is able to analyse complex traffic conditions better than the heuristic approach. The results show that this approach provides better results than the traditional image processing techniques.