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Vehicle Object Detection in Aerial Surveillance

Maheswari, Ramaswamy reddy

This paper presents vehicle object detection system in Aerial Surveillance. This system is helpful in the field of military recognize and traffic controlling system to automatic target recognition and tracking the moving Objects from the videos. We propose a vehicle detection frame work in two phases like training and Detection Phase. In this video is divided in to frames. We performing a pixel wise classification method among the neighbouring pixels in the regions of objects to obtaining the quantitative observations. Colour transforms are applied to separate vehicle and non-vehicle colours effectively. The Canny edge detection method applied to extract the local features of objects. Thus feature extraction process give exact results to classification by considering the vehicle colours and local features. Further Construct the Dynamic Bayesian network (DBN) for vehicle classification. The experiments conducted on a few varieties of aerial videos. The results demonstrate flexibility and good generalization abilities of the proposed system on a challenging data set with aerial surveillance images taken at different heights and under different camera angles.