• Biometrics
• Fingerprints
• VIS
• Europe
• Visa Information System

• EU-VIS
• Biometric Visa
• Biometric Evaluation Authority
• Monitoring
• Evaluation

• fingerprint
• betti number
• SIVV
• categorization

In this paper EEG signals are employed for the purpose of automatic user recognition. Specifically the resting state with closed eyes acquisition protocol has been here used and deeply investigated by varying the employed electrodes configuration both in number and location for optimizing the recognition performance still guaranteeing sufficient user convenience. A database of 45 healthy subjects has been employed in the analysis. Autoregressive stochastic modeling and polynomial regression based classification has been applied to extracted brain rhythms in order to identify the most distinctive contributions of the different subbands in the recognition process. Our analysis has shown that significantly high recognition rates, up to 98.73%, can be achieved when using proper triplets of electrodes, which cannot be achieved by employing couple of electrodes, whereas sets of five electrodes in the central posterior region of the scalp can guarantee very high recognition performance while limiting user convenience.

• Biometric template protection
• Biometric cryptosystems
• Multi-biometric fusion
• Fuzzy Commitment Scheme
• Fuzzy Vault

• iris recognition
• quality
• feature extraction

In accordance with the ISO/IEC FDIS 19794-6 standard an iris-biometric fusion of image metric-based and Hamming distance (HD) comparison scores is presented. In order to demonstrate the applicability of a knowledge transfer from image quality assessment to iris recognition, diverse image quality metrics are applied to iris textures, i.e. query textures are interpreted as noisy representations of registered ones. Obtained scores are fused with traditional HD scores obtained from iris-codes generated by different feature extraction algorithms. Experimental evaluations on the CASIA-v3 iris database confirm the soundness of the proposed approach.

Aadhaar is a national ID project being implemented in India towards issuing a Unique number to all the 1.2billion Indian residents. Biometrics has played a key role in the Aadhaar (UID) system in India, in order to ensure uniqueness during enrolment as well as for authentication for applications that aim to improve service delivery of government benefit schemes. This talk will focus on the design of the enrolment and authentication biometric system. The results of accuracy analysis of the enrolment and authentication systems will be covered.

• Authentication
• Biometrics
• Cameras
• Fingerphotos
• Smartphones

• Thomas Walther
• Jan Vana
• Shejin T
• Liming Chen
• Sum You Mok / Ajay Kuma
• Seira Hidano
• Abdel Ilah Salhi
• Andreas Nautsch
• Christophe Rosenberger
• Kam Yuen Cheng / Ajay Kumar
• Shigefumi Yamada
• Isao Nakanishi
• Kunal Goyal
• Sanjoy Paul
• Yufeng Zheng
• Laurent El Shafey
• Barry Guihen
• Hanene Guesmi
• Vincent Despiegel

• Face recognition
• border control
• evaluation

• Regions-of-interest
• Static Signature
• Signature Verificaton

• keystroke dynamics
• acquisition procedure
• statistical analysis,

• Person Re-Identification
• SURF Matching
• GMM Matching Pair Selection

• face detection
• face localization
• Local Binary Patterns
• Artificial Neural Network

• Object Localization
• Eye Localization
• Machine Learning
• Generalized Hough Transform

Face recognition based on 2D images is a widely used biometric approach. This is mainly due to the simplicity and high usability of this approach. Nonetheless, those solutions are vulnerable to spoof attacks made by non-real faces. In order to identify malicious attacks on such biometric systems, 2D face liveness detection approaches are developed. In this work, face liveness detection approaches are categorized based on the type of liveness indicator used. This categorization helps understanding different spoof attacks scenarios and their relation to the developed solutions. A review of the latest works dealing with face liveness detection works is presented. A discussion is made to link the state of the art solutions with the presented categorization along with the available and possible future datasets. All that aim to provide a clear path for the future development of innovative face liveness detection solutions.

• spoofing-attack
• Local Binary Patterns
• counter-measures

• session key
• key sharing
• secure key management
• revocable/cancelable biometrics
• crypto-biometrics keys

• forensic biometrics
• individualisation
• selection
• identification
• identity fraud

Vincent Despiegel, Safran Morpho

Raul Sanchez-Reillo, Universidad Carlos III de Madrid

Andreas Wolf, Bundesdruckerei