Title: Holistic knuckle recognition through adept texture representation

Authors: Neeru Bala; Anil Kumar; Rashmi Gupta; Ritesh Vyas

Addresses: Amity University Gurugram, Amity Education Valley Gurugram, Manesar, Panchgaon, Haryana-122412, India ' Amity University Gurugram, Amity Education Valley Gurugram, Manesar, Panchgaon, Haryana-122412, India ' Netaji Subhash University of Technology, East Campus, Geeta Colony, New Delhi, Delhi-110031, India ' Pandit Deendayal Energy University Knowledge Corridor, Raisan Village, Gandhinagar – 382426 Gujarat, India

Abstract: In topical years, substantiation of individuals through their finger knuckle patterns has turned into an extremely dynamic area of exploration. Finger knuckle patterns are the inimitable creases existent on the posterior surface of the hand, which is more expedient than other hand related modalities like fingerprint and palmprint, as the posterior surface of hand is less abraded in contrast to interior hand. This work presents an effective knuckle-based recognition framework via fusion of base, minor and major finger knuckle patterns of fingers of the individual for boosted recognition. For this, all the finger knuckle patterns are segmented and features are extracted explicitly using an efficient feature descriptor named curvature Gabor filter (CGF). In order to substantiate the proposed methodology, rigorous investigations have been performed on a publicly accessible large hand dorsal database named PolyU-Hand Dorsal (HD) dataset. Knuckles are integrated in three different ways to investigate the effect of their fusion, named 'fusion over knuckle', 'fusion over finger' and 'fusion over hand'. All the strategies mentioned have supported their magnified performance than individual knuckle recognition framework, whereas 'fusion over hand' outshined with tiniest EER of 0.2009.

Keywords: information security; multimodal biometrics; information fusion; knuckle recognition; score level fusion.

DOI: 10.1504/IJCVR.2025.142919

International Journal of Computational Vision and Robotics, 2025 Vol.15 No.1, pp.1 - 18

Received: 01 Apr 2022
Accepted: 18 Apr 2023
Published online: 02 Dec 2024 *

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