A Vehicle Detection Algorithm Based on Compressive Sensing and Background Subtraction

An efficient vehicle detection method is a necessity for the intelligent transportation system under the complicated traffic environment at present. To solve the problems of large computation and the poor real-time in traditional vehicle detecting methods, this article proposes a real-time vehicle detecting algorithm integrated compressive sensing (CS) theories and background subtraction method. In addition, this paper undertakes the reconstruction of foreground image of vehicle based on the orthogonal matching pursuit (OMP) algorithm. Proved by the experimental result, the proposed vehicle detection algorithm could produce higher precision detection, smaller calculation and higher-quality reconstructed image compared to the traditional ones.