教授 博士生导师 硕士生导师
性别: 男
毕业院校: 中国科技大学
学位: 博士
所在单位: 软件学院、国际信息与软件学院
学科: 计算机应用技术. 软件工程
电子邮箱: xczhang@dlut.edu.cn
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论文类型: 会议论文
发表时间: 2007-01-01
收录刊物: CPCI-S
页面范围: 68-+
摘要: A hybrid license plate segmentation approach based on neural network is proposed, which is designed to work under complex acquisition conditions including unrestricted scene and lighting and a wide range of camera-car distances. The approach consists Of four stages: preprocessing, candidate regions detecting, real vehicle license plate extracting, and character segmenting. Experiments have proved the robustness and accuracy of the approach. In the experiments databases, which were taken from real scenes, 380 from 400 images were successfully segmented. The average accuracy of segmenting vehicle license plate is 95%.