Title: LB and LT feature approach to personal identification using finger knuckle image biological trait
Authors: Brajesh Kumar Singh; Ravinder Kumar; R. Rama Kishore
Addresses: University School of Information and Communication Technology, GGSIP University, New Delhi, India ' Skill Faculty of Engineering and Technology, Shri Vishwakarma Skill University, Gurgaon, India ' University School of Information and Communication Technology, GGSIP University, New Delhi, India
Abstract: Biometric identification is an emerging field for personal authentication and has a large number of applications in the field of time attendance system and forensic domain. A variety of biometric traits are available, but among them, hand-based biometrics are more popular because of their ease of use and better performance. A lot of literature is available on fingerprint identification but it is observed that fingerprints are always not a reliable source of information to be captured from the crime scene to identify suspects. Therefore, it is required to use some other hand-based biological trait such as finger knuckle print (back side of finger joint skin pattern) in order to identify the suspect. This paper proposed a finger knuckle image-based person identification. The performance of the proposed biometric system is compared with the well-established fingerprint-based authentication system. The experiments were performed on the benchmark dataset like PolyU finger knuckle print dataset and FVC2002 fingerprint dataset. The experimental results show that the performance of the proposed algorithm leads over many fingerprint-based identification systems. The proposed algorithm can also be used to design finger knuckle image-based biometric systems instead of fingerprint-based biometric systems.
Keywords: biometric trait; finger knuckle print; fingerprint; biometric system; suspect identification.
International Journal of Electronic Security and Digital Forensics, 2021 Vol.13 No.4, pp.445 - 459
Received: 23 Apr 2020
Accepted: 02 Aug 2020
Published online: 06 Jul 2021 *