A Character-Based Method for License Plate Detection in Complex Scenes

摘要：

　　License plate detection is a crucial part in license plate recognition systems and is often considered as a solved problem.However,there are still plenty of complex scenes where the current methods are invalidated.In order to increase the performance in these scenes,we propose a novel character-based method to detect multiple license plates in complex images.Firstly,a preprocessing step is performed.Then we use a modified maximally stable extremal region(MSER)based detector called MSER-+ to detect the possible character regions.Some of the regions are removed according to their geographical information.Hierarchical morphology helps to connect candidate MSERs of various sizes.The regions satisfying some geographical limits will be fed into a convolutional neural network(CNN)model for further verification.Extensive experimental results validate that our method works well in a large variety of complex scenes.

关键词： Detection MSER-+ Hierarchical morphology Deep learning

作者: Dingyi Li Zengfu Wang

作者单位: Department of Automation,University of Science and Technology of China,Hefei 230027,China Department of Automation,University of Science and Technology of China,Hefei 230027,China;Institute

会议类型: 国际会议

会议名称: 第七届全国模式识别学术会议(The 7th Chinese Conference on Pattern Recognition,CCPR2016)

会议地点: 成都

会议语种:英文

页码: 576-587

在线出版日期: 2016-11-03（万方平台首次上网日期，不代表论文的发表时间）