Extraction of car license plate using motor vehicle regulation and character pattern recognition

Abstract

Extraction of car license plate is important for identifying a car. Since there are some problems such as poor ambient lighting problem, bad weather problem and so on, the car images can be distorted and the car license plate difficult to extract. This paper proposes a method of extracting car license plate using motor vehicle regulation. In this method, some features of car license plate according to motor vehicle regulation such as color information and shape are applied to determine the candidates of car license plates. To certify the license plate, the characters, numbers and their patterns are recognized by backpropagation neural networks in windows which are opened in those boundaries of candidates. For the results of recognition by neural networks, the candidate which has characters and numbers patterns according to motor vehicle regulation is certified as license-plate region. Since the results of characters-pattern recognition is used to certify the license plate, the ability of license-plate extracting is enhanced and the car is identified simultaneously. The results of the experiments with 70 samples of real car images show the performance of car license-plate extraction by 84.29%, and the recognition rate is 80.81%.