Please use this identifier to cite or link to this item: https://hdl.handle.net/10321/4169
Title: Contactless palmprint recognition system : a survey
Authors: Alausa, Dele W.S. 
Adetiba, Emmanuel
Badejo, Joke A. 
Davidson, Innocent E.
Obiyemi, Obiseye 
Buraimoh, Elutunji
Abayomi, Abdultaofeek
Oshin, Oluwadamilola 
Keywords: Biometrics;Information system;Palmprint images;Region of interest
Issue Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Source: Alausa, D.W.S. et al. 2022. Contactless palmprint recognition system: a survey. IEEE Access. : 1-1. doi:10.1109/access.2022.3193382
Journal: IEEE Access
Abstract: 
T Information systems in organizations traditionally require users to remember their secret pins
(password), token, card number, or both to confirm their identities. However, the technological trend has
been moving towards personal identification based on individual behavioural attributes (such as gaits,
signature, and voice) or physiological (such as palmprint, fingerprint, face, iris, or ear). These attributes
(biometrics) offer many advantages over knowledge and possession-based approaches. For example,
palmprint images have rich, unique features for reliable human identification, and it has received significant
attention due to their stability, reliability, uniqueness, and non-intrusiveness. This paper provides an overview
and evaluation of contactless palmprint recognition system, the state-of-the-art performance of existing
works, different types of "Region of Interest" (ROI) extraction algorithms, feature extraction, and matching
algorithms. Finally, the findings obtained are presented and discussed
URI: https://hdl.handle.net/10321/4169
ISSN: 2169-3536 (Online)
DOI: 10.1109/access.2022.3193382
Appears in Collections:Research Publications (Engineering and Built Environment)

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