{"title":"基于摄像头的在线签名采集生物识别身份验证方法","authors":"D. Muramatsu, Kumiko Yasuda, T. Matsumoto","doi":"10.1109/ICDAR.2009.112","DOIUrl":null,"url":null,"abstract":"A camera-based online signature verification system is proposed in this paper. One web camera is used for data acquisition, and a sequential Monte Carlo method is used for tracking a pen tip. Several distances are computed from an online signature, and a fusion model trained by using AdaBoost combines the distances and computes a final score.Preliminary experiments were performed by using a private database. The proposed system yielded an equal error rate (EER) of 4.0%.","PeriodicalId":433762,"journal":{"name":"2009 10th International Conference on Document Analysis and Recognition","volume":"22 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Biometric Person Authentication Method Using Camera-Based Online Signature Acquisition\",\"authors\":\"D. Muramatsu, Kumiko Yasuda, T. Matsumoto\",\"doi\":\"10.1109/ICDAR.2009.112\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A camera-based online signature verification system is proposed in this paper. One web camera is used for data acquisition, and a sequential Monte Carlo method is used for tracking a pen tip. Several distances are computed from an online signature, and a fusion model trained by using AdaBoost combines the distances and computes a final score.Preliminary experiments were performed by using a private database. The proposed system yielded an equal error rate (EER) of 4.0%.\",\"PeriodicalId\":433762,\"journal\":{\"name\":\"2009 10th International Conference on Document Analysis and Recognition\",\"volume\":\"22 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 10th International Conference on Document Analysis and Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDAR.2009.112\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 10th International Conference on Document Analysis and Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDAR.2009.112","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Biometric Person Authentication Method Using Camera-Based Online Signature Acquisition
A camera-based online signature verification system is proposed in this paper. One web camera is used for data acquisition, and a sequential Monte Carlo method is used for tracking a pen tip. Several distances are computed from an online signature, and a fusion model trained by using AdaBoost combines the distances and computes a final score.Preliminary experiments were performed by using a private database. The proposed system yielded an equal error rate (EER) of 4.0%.
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