中南民族大学学报（自然科学版）2017，Vol.36Issue(3)：125-130,6.
基于CNN的车牌识别系统
License Plate Recognition System Based on CNN
摘要
Abstract
The existing license plate recognition system is difficult to locate and identify the license plate effectively when it encounters complex conditions such as dim light, plate is blocked, multiple plates and low visibility. An automatic license plate recognition system based on convolution neural network ( CNN) has been proposed in this paper. In the license plate location phase, three kinds of positioning methods are integrated for the initial locating of the license plate. Then, the CNN model is used to judge the selected license plate. In the license plate character recognition phase, segmented characters are input to a designed CNN model, and the output of the CNN model is the result of the recognized characters. The experiment is based on 5906 license plate images and non-license plate images, and 36261 characters images. The results of the experiment show that the recognition rates of the proposed system for license plate and character are 94% and 96. 4%respectively, which is significantly better than that of traditional license plate recognition methods. It meets the needs of the vast majority of the use of the scene, with a high practicality.关键词
车牌定位/车牌识别/字符识别/卷积神经网络Key words
license plate locating/license plate recognize/character recognize/CNN分类
信息技术与安全科学引用本文复制引用
徐胜舟,周煜..基于CNN的车牌识别系统[J].中南民族大学学报（自然科学版）,2017,36(3):125-130,6.基金项目
国家自然科学基金资助项目(61302192) （61302192）
