2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications最新文献

Missing data estimation in multi-biometric identification and verification 多生物特征识别与验证中的缺失数据估计

2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications Pub Date : 2013-11-07 DOI: 10.1109/BIOMS.2013.6656147

N. Damer, Benedikt Fuhrer, Arjan Kuijper

引用次数: 10

Influence of QT correction on temporal and amplitude features for human identification via ECG QT校正对心电图人体识别的时间和振幅特征的影响

2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications Pub Date : 2013-11-07 DOI: 10.1109/BIOMS.2013.6656144

M. Sansone, A. Fratini, M. Cesarelli, P. Bifulco, A. Pepino, M. Romano, F. Gargiulo, Carlo Sansone

引用次数: 11

Exploiting cohorts information in multibiometric identification systems via graph-based fusion 利用基于图形融合的多生物特征识别系统中的队列信息

2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications Pub Date : 2013-11-07 DOI: 10.1109/BIOMS.2013.6656146

Emanuela Marasco, Carlo Sansone

引用次数: 0

A preliminary study on continuous authentication methods for photoplethysmographic biometrics 光容积脉搏波生物特征连续认证方法的初步研究

2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications Pub Date : 2013-11-07 DOI: 10.1109/BIOMS.2013.6656145

Angelo Bonissi, R. D. Labati, Luca Perico, R. Sassi, F. Scotti, Luca Sparagino

引用次数: 60

Fingerprint liveness detection based on Weber Local image Descriptor 基于Weber局部图像描述符的指纹活跃度检测

2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications Pub Date : 2013-11-07 DOI: 10.1109/BIOMS.2013.6656148

Diego Gragnaniello, G. Poggi, Carlo Sansone, L. Verdoliva

引用次数: 131

Creating synthetic IrisCodes to feed biometrics experiments 创建合成虹膜代码来进行生物识别实验

2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications Pub Date : 2013-11-07 DOI: 10.1109/BIOMS.2013.6656141

Hugo Proença, J. Neves

{"title":"Creating synthetic IrisCodes to feed biometrics experiments","authors":"Hugo Proença, J. Neves","doi":"10.1109/BIOMS.2013.6656141","DOIUrl":"https://doi.org/10.1109/BIOMS.2013.6656141","url":null,"abstract":"The collection of iris data suitable to be used in experiments is difficult, mainly due to two factors: 1) the time spent by volunteers in the acquisition process; and 2) security / privacy concerns of volunteers. Even though there are methods to create images of artificial irises, there is no method exclusively focused in the synthesis of the iris biometric signatures (IrisCodes). In experiments related with some phases of the biometric recognition process (e.g., indexing / retrieval), a large number of signatures is required for proper evaluation, which, in case of real data, is extremely hard to obtain. Hence, this paper describes a stochastic method to synthesize IrisCodes, based on the notion of data correlation. These artificial signatures can be used to feed experiments on iris recognition, namely on the iris matching, indexing and retrieval phases. We experimentally confirmed that both the genuine and impostor distributions obtained on the artificial data closely resemble the values obtained in data sets of real irises. Finally, another interesting feature is that the method is easily parametrized to mimic IrisCodes extracted from data of varying levels of quality, i.e., ranging from data acquired in high controlled to unconstrained environments.","PeriodicalId":409073,"journal":{"name":"2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115177733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Feature point validation for improved retina recognition 改进视网膜识别的特征点验证

2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications Pub Date : 2013-11-07 DOI: 10.1109/BIOMS.2013.6656142

Joddat Fatima, Adeel M. Syed, M. Akram

引用次数: 12

FAME: Face Authentication for Mobile Encounter FAME:移动相遇的人脸认证

2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications Pub Date : 2013-11-07 DOI: 10.1109/BIOMS.2013.6656140

Silvio Barra, Maria De Marsico, Chiara Galdi, D. Riccio, H. Wechsler

{"title":"FAME: Face Authentication for Mobile Encounter","authors":"Silvio Barra, Maria De Marsico, Chiara Galdi, D. Riccio, H. Wechsler","doi":"10.1109/BIOMS.2013.6656140","DOIUrl":"https://doi.org/10.1109/BIOMS.2013.6656140","url":null,"abstract":"The use of mobile devices is continuously growing, together with their ability to store and exchange sensitive data. This has spurred the interest, from one side, in exploiting their apparent vulnerabilities, and on the other side, in protecting users from any malfeasance. In this scenario, it has become essential to develop and deploy secure access and identification protocols on mobile platforms. Another emerging aspect that also needs attention bears on the commercial and social use of identity management systems. Towards such ends, this paper proposes using biometrics as the technology of choice, and describes FAME (Face Authentication for Mobile Encounters). FAME is an embedded application for mobile devices that provides both verification and identification, including identity management to support social activities, e.g., finding doubles in a social network. Such functionalities are implemented subject to privacy and security concerns. FAME cascade architecture is modular. The single modules perform image acquisition, anti-spoofing, face detection, face segmentation, feature extraction, and face matching. FAME also provides continuous recognition and best biometric sample selection, that both accommodate varying pose and illumination. All procedures are optimized for mobile use, using low-demanding and computation-light algorithms. Preliminary questionnaires administered to users engaged with using FAME show user acceptance, ease of use, and reliability.","PeriodicalId":409073,"journal":{"name":"2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127733085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 17

Temporal and spectral features of single lead ECG for human identification 用于人体识别的单导联心电图的时间和频谱特征

2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications Pub Date : 2013-11-07 DOI: 10.1109/BIOMS.2013.6656143

A. Kaveh, Wayne Chung

引用次数: 19