A vehicle recognition method robust against vehicles' overlapping based on stereo vision

For the purpose of traffic measurement, it is necessary to recognize various vehicles, including those vehicles that are partly overlapped. A new stereo-based image processing vehicle recognition method which is robust against vehicles' overlapping, is proposed. A stereo-based method is selected because of its robustness to environmental changes. The proposed method overcomes the problem by three key points: 1) feature extraction based on a size-changeable feature extraction window; 2) camera calibration using environmental information; and 3) model matching with various overlapped vehicles' models. The effectiveness of the proposed method has been confirmed by experiments on real images. An average recognition accuracy rate above 95% was obtained for images of frequently overlapped vehicles.