32 research outputs found
An Embedded Biometric Sensor for Ubiquitous Authentication
Communication networks and distributed technologies
move people towards the era of ubiquitous computing. An
ubiquitous environment needs many authentication sensors for
users recognition, in order to provide a secure infrastructure for
both user access to resources and services and information
management. Today the security requirements must ensure
secure and trusted user information to protect sensitive data
resource access and they could be used for user traceability inside
the platform. Conventional authentication systems, based on
username and password, are in crisis since they are not able to
guarantee a suitable security level for several applications.
Biometric authentication systems represent a valid alternative to
the conventional authentication systems providing a flexible einfrastructure
towards an integrated solution supporting the
requirement for improved inter-organizational functionality. In
this work the study and the implementation of a fingerprintsbased
embedded biometric system is proposed. Typical strategies
implemented in Identity Management Systems could be useful to
protect biometric information. The proposed sensor can be seen
as a self-contained sensor: it performs the all elaboration steps on
board, a necessary requisite to strengthen security, so that
sensible data are securely managed and stored inside the sensor,
without any data leaking out. The sensor has been prototyped via
an FPGA-based platform achieving fast execution time and a
good final throughput. Resources used, elaboration times of the
sensor are reported. Finally, recognition rates of the proposed
embedded biometric sensor have been evaluated considering
three different databases: the FVC2002 reference database, the
CSAI/Biometrika proprietary database, and the CSAI/Secugen
proprietary database. The best achieved FAR and FRR indexes
are respectively 1.07% and 8.33%, with an elaboration time of
183.32 ms and a working frequency of 22.5 MHz
An Efficient Reconfigurable Architecture for Fingerprint Recognition
The fingerprint identification is an efficient biometric technique to authenticate human beings in real-time Big Data Analytics. In this paper, we propose an efficient Finite State Machine (FSM) based reconfigurable architecture for fingerprint recognition. The fingerprint image is resized, and Compound Linear Binary Pattern (CLBP) is applied on fingerprint, followed by histogram to obtain histogram CLBP features. Discrete Wavelet Transform (DWT) Level 2 features are obtained by the same methodology. The novel matching score of CLBP is computed using histogram CLBP features of test image and fingerprint images in the database. Similarly, the DWT matching score is computed using DWT features of test image and fingerprint images in the database. Further, the matching scores of CLBP and DWT are fused with arithmetic equation using improvement factor. The performance parameters such as TSR (Total Success Rate), FAR (False Acceptance Rate), and FRR (False Rejection Rate) are computed using fusion scores with correlation matching technique for FVC2004 DB3 Database. The proposed fusion based VLSI architecture is synthesized on Virtex xc5vlx30T-3 FPGA board using Finite State Machine resulting in optimized parameters
Fingerprint Liveness Detection using Minutiae-Independent Dense Sampling of Local Patches
Fingerprint recognition and matching is a common form of user authentication.
While a fingerprint is unique to each individual, authentication is vulnerable
when an attacker can forge a copy of the fingerprint (spoof). To combat these
spoofed fingerprints, spoof detection and liveness detection algorithms are
currently being researched as countermeasures to this security vulnerability.
This paper introduces a fingerprint anti-spoofing mechanism using machine
learning.Comment: Submitted, peer-reviewed, accepted, and under publication with
Springer Natur
An FPGA-based Embedded System For Fingerprint Matching Using Phase Only Correlation Algorithm
none5There is an increasing interest in inexpensive and reliable personal identification in many emerging civilian, commercial and financial applications.
Traditional systems such as passwords, PINs, Badges, Smart Cards and Tokens may either be stolen or easy to guess but also to forget, in same cases they may be lost by the user who carries them; all this can lead to identified.
Fingerprint-based identification is one of the most used biometric techniques in automated systems for personal identification and it is becoming socially acceptable and cost-effective, since a fingerprint is univocally related to a particular individual.
Typical fingerprint identification methods employ feature-based image matching, where minutiae points in the ridge lines (i.e., ridge endings and bifurcations) are identified. Unfortunately this approach is highly influenced by fingertip surface condition.
Fingerprint recognition is a complex pattern recognition problem. The efforts to make automatic the matching process based on digital representation of fingerprints, led to the development of Automatic Fingerprint Identification Systems (AFIS). Typically, there are millions of fingerprint records in a database which needs to be entirely searched for a match, to establish the identity of the individual.
In order to provide a reasonable response time for each query, it will be better to develop special hardware solutions to implement matching and/or classification algorithms in a really efficient way.
In this work we realised a system able to outperform modern PCs in recognising and classifying fingerprints and based on FPGA technology.Il lavoro si è classificato al II posto nell'Altera Contest 2009 Innovate Italy, gara annuale indetta da Altera tra progetti di team di giovani studenti universitari su tutto il territorio nazionale.Giovanni Danese; Mauro Giachero; Francesco Leporati; Giulia Matrone; Nelson NazzicariDanese, Giovanni; Giachero, Mauro; Leporati, Francesco; Matrone, Giulia; Nelson, Nazzicar