{"title":"基于高斯-埃尔米特矩的车牌字符识别","authors":"Xiaojuan Ma, Renlong Pan, Lin Wang","doi":"10.1109/ETCS.2010.591","DOIUrl":null,"url":null,"abstract":"Character recognition plays an important role in the automatic license plate recognition (ALPR) system. In this paper, we propose a new method to recognize the license plates characters by using 2D Gaussian-Hermite moments (GHMs) of different orders with 231 GHMs features as the input vector of BP neural network. The system worked under variable illumination, variable size of plate and dynamic backgrounds. The experimental results demonstrate robust and efficient of our method.","PeriodicalId":193276,"journal":{"name":"2010 Second International Workshop on Education Technology and Computer Science","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"License Plate Character Recognition Based on Gaussian-Hermite Moments\",\"authors\":\"Xiaojuan Ma, Renlong Pan, Lin Wang\",\"doi\":\"10.1109/ETCS.2010.591\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Character recognition plays an important role in the automatic license plate recognition (ALPR) system. In this paper, we propose a new method to recognize the license plates characters by using 2D Gaussian-Hermite moments (GHMs) of different orders with 231 GHMs features as the input vector of BP neural network. The system worked under variable illumination, variable size of plate and dynamic backgrounds. The experimental results demonstrate robust and efficient of our method.\",\"PeriodicalId\":193276,\"journal\":{\"name\":\"2010 Second International Workshop on Education Technology and Computer Science\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-03-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Second International Workshop on Education Technology and Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ETCS.2010.591\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Workshop on Education Technology and Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETCS.2010.591","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
License Plate Character Recognition Based on Gaussian-Hermite Moments
Character recognition plays an important role in the automatic license plate recognition (ALPR) system. In this paper, we propose a new method to recognize the license plates characters by using 2D Gaussian-Hermite moments (GHMs) of different orders with 231 GHMs features as the input vector of BP neural network. The system worked under variable illumination, variable size of plate and dynamic backgrounds. The experimental results demonstrate robust and efficient of our method.
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