State of the art and perspectives on traditional and emerging biometrics: A survey

Traoré, Issa; Alshahrani, Mohammed Mujib; Obaidat, Mohammad S.

doi:10.1002/spy2.44

Cited by 13 publications

(15 citation statements)

References 164 publications

(211 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These metrics attempt to identify the mechanism's sensitivity in distinguishing between genuine users and imposters.Over time, variability in biometric features sets poses serious challenges for biometric systems to genuinely identify genuine users from imposters or vice versa. Previous research [32][33][34][35] on biometric systems has used performance indices such as the False Acceptance Rate (FAR), False Rejection Rate (FRR), and Equal Error Rate (EER) to evaluate the performance of biometric mechanisms. FAR and FRR, on the other hand, are evaluated by varying the score threshold to the similarity score.…”

Section: Performance Evaluationmentioning

confidence: 99%

Development of a Hybrid Radio Frequency Identification (RFID) and Biometric Based Library Management System

Okubanjo

Okandeji

Osifeko

et al. 2022

Gazi University Journal of Science

View full text Add to dashboard Cite

Highlights• This paper focuses on the smart library management system.• Integration of the LMS with biometric and RFID has been addressed.• The challenges on the conventional method of LMS and security issues are presented.• Integration of an LMS with internet-of-things, SMS, and email alert has been explained.• The system performance evaluation based on the error rate has been discussed.

show abstract

Section: Performance Evaluationmentioning

confidence: 99%

Development of a Hybrid Radio Frequency Identification (RFID) and Biometric Based Library Management System

Okubanjo

Okandeji

Osifeko

et al. 2022

Gazi University Journal of Science

View full text Add to dashboard Cite

show abstract

“…However, what used to require sophisticated machinery can now be done with the average smart-phone (Galdi et al, 2016). In addition to these identification biometrics, smartphones can now capture upwards of two thousand behavioural biometrics (Traore et al, 2018). These behavioural biometrics include how the device is held, how the individual applies pressure when typing, scrolling style and toggling between fields (Hinckley et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

Al-enabled biometrics in recruiting: Insights from marketers for managers

Esch

Black²,

Franklin

et al. 2020

Australasian Marketing Journal

View full text Add to dashboard Cite

Both researchers and practitioners are only in the early stages of examining and understanding the application of artificial intelligence (AI) in terms of marketing themselves as employers or the open jobs they have. AI has the potential to significantly affect how firms reach, identify, attract, and select human capital. We examine factors that can influence a job candidate's intent to complete AI-enabled recruiting processes, especially the influence of a firm's use of biometrics in that process. The results show that (1) social media can increase technology use motivation and AI-enabled recruiting with (2) trendiness as a first stage boundary condition and (3) biometrics as a second stage boundary condition. We contribute to marketing knowledge by identifying that for managers wanting to influence job seekers’ technology use motivation in order to increase their participation in AI-enabled recruiting; they must focus on the indirect effects of trendiness, biometrics, and their social media usage.

show abstract

“…One of the methods of person verification utilizes the near-infrared (NIR) images of the finger vascular system, which is proved to contain a set of features unique for each human. External features, like a fingerprint, finger shape, skin folds and lunulas are accompanied by the internal features-the structure of a vascular system [1]. Finger tissues and blood have different absorption coefficients for various light wavelengths which phenomenon allows for observation of both types of features in NIR images.…”

Section: Introductionmentioning

confidence: 99%

Modified Distance Transformation for Image Enhancement in NIR Imaging of Finger Vein System

Bernacki

Moroń

2020

Sensors

View full text Add to dashboard Cite

Most of the current image processing methods used in the near-infrared imaging of finger vascular system concentrate on the extraction of internal structures (veins). In this paper, we propose a novel approach which allows to enhance both internal and external features of a finger. The method is based on the Distance Transformation and allows for selective extraction of physiological structures from an observed finger. We evaluate the impact of its parameters on the effectiveness of the already established processing pipeline used for biometric identification. The new method was compared with five state-of-the-art approaches to features extraction (position-gray-profile-curve—PGPGC, maximum curvature points in image profiles—MC, Niblack image adaptive thresholding—NAT, repeated dark line tracking—RDLT, and wide line detector—WD) on the GustoDB database of images obtained in a wide range of NIR wavelengths (730–950 nm). The results indicate a clear superiority of the proposed approach over the remaining alternatives. The method managed to reach over 90 % identification accuracy for all analyzed datasets.

show abstract

State of the art and perspectives on traditional and emerging biometrics: A survey

Cited by 13 publications

References 164 publications

Development of a Hybrid Radio Frequency Identification (RFID) and Biometric Based Library Management System

Development of a Hybrid Radio Frequency Identification (RFID) and Biometric Based Library Management System

Al-enabled biometrics in recruiting: Insights from marketers for managers

Modified Distance Transformation for Image Enhancement in NIR Imaging of Finger Vein System

Contact Info

Product

Resources

About