Image Processing Based Vehicle Detection and Tracking: A Comparative Study

Abstract

With the increasing economical-developments and urban population, the number of vehicles on road is increasing as well and hence the traffic. There comes the need to lower the congestion of roads caused due to vehicular traffic. Out of numerous vehicle detection and tracking techniques, this paper deals with Image- processing-based methods simulated using MATLAB Simulink. Few such methods are Background subtraction with gaussian and Kalman Filter, Blob analysis, Horn- Schunck, Particle Filter and Monte Carlo method. Background subtraction is the most familiar one these days followed by the Morphological operations. It depends on certain parameters like accuracy, time for processing, segmenting, and complexity. The various traffic parameters like the speed of the car, count, and its tracking are calculated using its threshold values in some of the detection methods. The work proposed is done in real-time taking the challenging examples. The results mentioned throw light on the lustiness of the study proposed.