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In this paper we present a full-featured license plate detection and recognition system. The system is implemented on an embedded DSP platform and processes a video stream in real-time. It consists of a detection and a character recognition module. The detector is based on the AdaBoost approach presented by Viola and Jones. Detected license plates are segmented into individual characters by using a region-based approach. Character classification is performed with support vector classification. In order to speed up the detection process on the embedded device, a Kalman tracker is integrated into the system. The search area of the detector is limited to locations where the next location of a license plate is predicted. Furthermore, classification results of subsequent frames are combined to improve the class accuracy. The major advantages of our system are its real-time capability and that it does not require any additional sensor input (e.g. from infrared sensors) except a video stream. We evaluate our system on a large number of vehicles and license plates using bad quality video and show that the low resolution can be partly compensated by combining classification results of subsequent frames.
Arth et al. (Fri,) studied this question.