Bagas Sakamulia Prakoso, Ivanna K. Timotius, Iwan Setyawan
{"title":"基于线检测和局部标准差的用户验证掌纹识别","authors":"Bagas Sakamulia Prakoso, Ivanna K. Timotius, Iwan Setyawan","doi":"10.1109/ICITACEE.2014.7065733","DOIUrl":null,"url":null,"abstract":"Human palmprints contain biometric features that can be used to identify an individual. These features can be used for example in user verification applications. This paper presents a user verification system using palmprint identification. The image of the palm is captured using a web camera. Then the features used for palmprint identification is extracted using line detection and local standard deviation. The proposed system is evaluated by asking 40 subjects to act as users (10 subject as registered users and 30 non-registered users). Our experiments show that the system can achieve accuracy rate of up to 98% with no false acceptance and 2% false rejection rate. The average time required to perform a user verification is 340 ms.","PeriodicalId":404830,"journal":{"name":"2014 The 1st International Conference on Information Technology, Computer, and Electrical Engineering","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Palmprint identification for user verification based on line detection and local standard deviation\",\"authors\":\"Bagas Sakamulia Prakoso, Ivanna K. Timotius, Iwan Setyawan\",\"doi\":\"10.1109/ICITACEE.2014.7065733\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Human palmprints contain biometric features that can be used to identify an individual. These features can be used for example in user verification applications. This paper presents a user verification system using palmprint identification. The image of the palm is captured using a web camera. Then the features used for palmprint identification is extracted using line detection and local standard deviation. The proposed system is evaluated by asking 40 subjects to act as users (10 subject as registered users and 30 non-registered users). Our experiments show that the system can achieve accuracy rate of up to 98% with no false acceptance and 2% false rejection rate. The average time required to perform a user verification is 340 ms.\",\"PeriodicalId\":404830,\"journal\":{\"name\":\"2014 The 1st International Conference on Information Technology, Computer, and Electrical Engineering\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 The 1st International Conference on Information Technology, Computer, and Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICITACEE.2014.7065733\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 The 1st International Conference on Information Technology, Computer, and Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICITACEE.2014.7065733","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Palmprint identification for user verification based on line detection and local standard deviation
Human palmprints contain biometric features that can be used to identify an individual. These features can be used for example in user verification applications. This paper presents a user verification system using palmprint identification. The image of the palm is captured using a web camera. Then the features used for palmprint identification is extracted using line detection and local standard deviation. The proposed system is evaluated by asking 40 subjects to act as users (10 subject as registered users and 30 non-registered users). Our experiments show that the system can achieve accuracy rate of up to 98% with no false acceptance and 2% false rejection rate. The average time required to perform a user verification is 340 ms.