{"title":"双重生物特征认证方案,保护隐私","authors":"K. Sasireka, R. Rajesh","doi":"10.1109/CNT.2014.7062734","DOIUrl":null,"url":null,"abstract":"Preserving the privacy of biometric data becomes a critical work. To increase the privacy of the biometric data, novel method is proposed. In this proposed method, two different biometric data such as features from fingerprint and face are combined. In the face, the features like eyes, lips and brow are extracted. In the fingerprint, orientation feature is extracted. The database contains the training images. The ELM classifier is used to combine these features and matches with the training image.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"146 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Dual biometric authentication scheme for privacy protection\",\"authors\":\"K. Sasireka, R. Rajesh\",\"doi\":\"10.1109/CNT.2014.7062734\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Preserving the privacy of biometric data becomes a critical work. To increase the privacy of the biometric data, novel method is proposed. In this proposed method, two different biometric data such as features from fingerprint and face are combined. In the face, the features like eyes, lips and brow are extracted. In the fingerprint, orientation feature is extracted. The database contains the training images. The ELM classifier is used to combine these features and matches with the training image.\",\"PeriodicalId\":347883,\"journal\":{\"name\":\"2014 International Conference on Communication and Network Technologies\",\"volume\":\"146 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Communication and Network Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CNT.2014.7062734\",\"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 International Conference on Communication and Network Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CNT.2014.7062734","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dual biometric authentication scheme for privacy protection
Preserving the privacy of biometric data becomes a critical work. To increase the privacy of the biometric data, novel method is proposed. In this proposed method, two different biometric data such as features from fingerprint and face are combined. In the face, the features like eyes, lips and brow are extracted. In the fingerprint, orientation feature is extracted. The database contains the training images. The ELM classifier is used to combine these features and matches with the training image.