The paper presents a real time image processing algorithm for distance estimation on Beagleboard. The system uses a single camera fixed at a stationary position to capture the real time image of target object and determine its distance in contrast to existing and most common vision algorithms of stereo vision.The image captured from a single forward facing camera suffers from high degree of uncertainty in object distance estimation due to the nonlinear relation between object height and its actual distance from camera. This uncertainty is eliminated by using Inverse Perspective Mapping to translate the front view captured by the photosensitive sensor to a bird's eye view. The focus of the paper is to present a statistical approach to scale the position of object in pixel to the real world physical distance. The proposed algorithm offers high efficiency in determining the distance of target object in a short time and thus aids the autonomous vehicle in intelligent navigation and feedback. The implementation is done using Intel OpenCV image processing libraries to reduce system overhead and is intended to work at least at 30 fps with VGA resolution.

The paper presents a real time traffic monitoring system that makes use of image processing algorithm to detect and estimate the of count of vehicles using motion detection approach. Traffic congestion is a serious issue, which is the root cause of a series of serious problems. Conventional traffic light controllers have limitations because they make use of the predefined hardware, whose functioning is governed according to program that does not have the flexibility of modification on real time basis. The proposed system makes use of a differential algorithm in order to determine the signaling duration of each lane of intersection. The system provides different delays for different junctions thus optimizing the waiting time of each user. This flexibility of timing and controlling prevents the congestion of vehicles in squares due to high waiting time for the green light. The traffic flux density determines the effective number of vehicles at any intersection and hence is critical in allocation of signaling duration to any intersection. Real time analysis presents many challenges in video analysis and in order to lower down the computational complexities, the algorithm makes use of simple background subtraction technique. The system has been tested for a number of video sequences. The results produced are extremely encouraging and hence the system can be applied in real time traffic control in urban areas.

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