The recognition of car license plate for automatic parking system

The recognition of a car's license plate for an automatic parking system is important for identifying the car at the entrance of the parking area because the car license plate has unique information for each car. This paper proposes the recognition of car license plate which is accurate and robust to environmental variation by using the car's license plate patterns according to motor vehicle regulation and a 4-layer BP neural network with supervised learning. In this method, the candidates regions of the car license plate are determined approximately according to the car license plate regulation such as color, the ratio and shape of the car license plate, the pattern of characters and numbers etc. For the results of recognition by neural networks, the candidate that has characters and numbers according to motor vehicle regulation is certified as license-plate region. Since the results of characters-pattern recognition are used to certify the license plate, the ability of license plate extraction is more accurate and the car can be identified simultaneously. The experimental results of seventy car images with the prototype of the automatic parking system show the performance of car license plate extraction rate of 96%, and the recognition rate is 92%.