{"title":"一种银行卡卡号自动定位与识别方法","authors":"Yuanxue Xin, P. Shi, Song Han","doi":"10.1145/3366194.3366325","DOIUrl":null,"url":null,"abstract":"The Optical Character Recognition (OCR) technology is widely used in intelligent identification of bank cards, since it can improve the work efficiency and user experience in mobile payment. Conventional methods have the problems of low recognition rate and location accuracy. Therefore, an automatic location and recognition method for bank card number is proposed. Firstly, novel Connected Text Proposal Network (CTPN) algorithm is improved to locate the bank card number. Then, the Convolutional Recurrent Neural Networks (CRNN) algorithm is optimized to identify the card number. Some experimental results show that the method has a high positioning accuracy and recognition rate.","PeriodicalId":105852,"journal":{"name":"Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An Automatic Location and Recognition Method for Bank Card Number\",\"authors\":\"Yuanxue Xin, P. Shi, Song Han\",\"doi\":\"10.1145/3366194.3366325\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Optical Character Recognition (OCR) technology is widely used in intelligent identification of bank cards, since it can improve the work efficiency and user experience in mobile payment. Conventional methods have the problems of low recognition rate and location accuracy. Therefore, an automatic location and recognition method for bank card number is proposed. Firstly, novel Connected Text Proposal Network (CTPN) algorithm is improved to locate the bank card number. Then, the Convolutional Recurrent Neural Networks (CRNN) algorithm is optimized to identify the card number. Some experimental results show that the method has a high positioning accuracy and recognition rate.\",\"PeriodicalId\":105852,\"journal\":{\"name\":\"Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3366194.3366325\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3366194.3366325","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Automatic Location and Recognition Method for Bank Card Number
The Optical Character Recognition (OCR) technology is widely used in intelligent identification of bank cards, since it can improve the work efficiency and user experience in mobile payment. Conventional methods have the problems of low recognition rate and location accuracy. Therefore, an automatic location and recognition method for bank card number is proposed. Firstly, novel Connected Text Proposal Network (CTPN) algorithm is improved to locate the bank card number. Then, the Convolutional Recurrent Neural Networks (CRNN) algorithm is optimized to identify the card number. Some experimental results show that the method has a high positioning accuracy and recognition rate.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
