Template characterization and correlation algorithm created from segmentation for the iris biometric authentication based on analysis of textures implemented on a FPGA

Giacometto, F.; Vilardy, Juan M.; Torres, Cesar; Mattos, Lorenzo

doi:10.1088/1742-6596/274/1/012043

“…There is a lot of research also tried to make a hardware implementation of many biometric identification systems on FPGA or DSP such as the following. In (Giacometto et al, 2011) proposed an implementation of an algorithm characterization and correlation of templates created for biometric authentication based on iris texture analysis programmed on FPGA.…”

Section: Related Workmentioning

confidence: 99%

User Authentication based on Dynamic Keystroke Recognition

Fouad

¹

,

Hassan

²

,

Hassan

³

2016

International Journal of Ambient Computing and Intelligence

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Biometric identification is a very good candidate technology, which can facilitate a trusted user authentication with minimum constraints on the security of the access point. However, most of the biometric identification techniques require special hardware, thus complicate the access point and make it costly. Keystroke recognition is a biometric identification technique which relies on the user behavior while typing on the keyboard. It is a more secure and does not need any additional hardware to the access point. This paper presents a developed behavioral biometric authentication method which enables to identify the user based on his Keystroke Static Authentication (KSA) and describes an authentication system that explains the ability of keystroke technique to authenticate the user based on his template profile saved in the database. Also, an algorithm based on dynamic keystroke analysis has been presented, synthesized, simulated and implemented on Field Programmable Gate Array (FPGA). The proposed algorithm is tested on 25 individuals, achieving a False Rejection Rate (FRR) about 4% and a False Acceptance Rate (FAR) about 0%. This performance is reached using the same sampling text for all the individuals. In this paper, two methods are used to implement the proposed approach: method one (H/W based Sorter) and method two (S/W based Sorter) are achieved execution time about 50.653 ns and 9.650 ns, respectively. Method two achieved a lower execution time; the time in which the proposed algorithm is executed on FPGA board, compared to some published results. As the second method achieved a small execution time and area utilization so it is the preferred method to be implemented on FPGA.

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Software implementation of the OSIRIS iris recognition algorithm in FPGA

Hentati

¹

,

Abid

²

,

Dorizzi

³

2011

ICM 2011 Proceeding

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International audienceIn this paper, we present a software implementation of an iris recognition algorithm on a FPGA (Field Programmable Gate Array). We use the OSIRIS reference systems developed in the framework of the BioSecure project which is an implementation of the well-knoun Daugman approach [10]. This system is composed of two modules. The first one uses the Hough transform to segment and normalize the iris. The second module applies a Gabor filter on the normalized image and calculates the similarity score between two images using the Hamming distance. OSIRIS algorithm has performance (EER=7.04%) when it is running on the PC in ICE 2005 Database. This system is coded in C++ using the library OpenCV (Open Source Computer Vision). This library is difficult to implement it in FPGA. that's why, we first remove this library in our code than improve this algorithm. Finally, we implement it on a CYCLONE II DE2 Board FPGA using the NIOS II processor which is characterized by its flexibility and programmability

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User Authentication Based on Dynamic Keystroke Recognition

Fouad

¹

,

Hassan

²

,

³

View full text Add to dashboard Cite

Biometric identification is a very good candidate technology, which can facilitate a trusted user authentication with minimum constraints on the security of the access point. However, most of the biometric identification techniques require special hardware, thus complicate the access point and make it costly. Keystroke recognition is a biometric identification technique which relies on the user behavior while typing on the keyboard. It is a more secure and does not need any additional hardware to the access point. This paper presents a developed behavioral biometric authentication method which enables to identify the user based on his Keystroke Static Authentication (KSA) and describes an authentication system that explains the ability of keystroke technique to authenticate the user based on his template profile saved in the database. Also, an algorithm based on dynamic keystroke analysis has been presented, synthesized, simulated and implemented on Field Programmable Gate Array (FPGA). The proposed algorithm is tested on 25 individuals, achieving a False Rejection Rate (FRR) about 4% and a False Acceptance Rate (FAR) about 0%. This performance is reached using the same sampling text for all the individuals. In this paper, two methods are used to implement the proposed approach: method one (H/W based Sorter) and method two (S/W based Sorter) are achieved execution time about 50.653 ns and 9.650 ns, respectively. Method two achieved a lower execution time; the time in which the proposed algorithm is executed on FPGA board, compared to some published results. As the second method achieved a small execution time and area utilization so it is the preferred method to be implemented on FPGA.

show abstract

Template characterization and correlation algorithm created from segmentation for the iris biometric authentication based on analysis of textures implemented on a FPGA

Cited by 3 publications

References 1 publication

User Authentication based on Dynamic Keystroke Recognition

User Authentication based on Dynamic Keystroke Recognition

Software implementation of the OSIRIS iris recognition algorithm in FPGA

User Authentication Based on Dynamic Keystroke Recognition

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