Algorithm for vision-based vehicle detection and classification

Recent years, many vision-based vehicle detection methods have been proposed. But just a few of them paid attention to vehicle type classification in a real-time video, which is an important part in intelligent traffic system. The Haar features and Histograms of Oriented Gradients (HOG) features have been proposed as useful features for vehicle detection respectively. In this paper, we propose a method based on combined the Haar features and HOG features to detect vehicles in videos and classify them into two types. The experiment results show that this method can classify and detect the vehicles in multi-orientations with good classification results, and it verified the effectiveness of the propose method with real vehicle samples.