The increasing terrorist and criminal acts on public, private, and government infrastructure have resulted in a chaotic situation, thereby putting the surveillance system in existence under pressure. Conventionally, information systems rely on users to remember their secret pins (passwords) or tokens, cards, or both to confirm their identity. In order to achieve this in modern times, personal identification is based on the behavioral or physiological traits of individuals. These attributes known as biometrics refer to the unique physiological (e.g., palmprint, fingerprint, face, iris, etc.) or behavioral (e.g., gaits, signature, voice, etc.) traits used for automatic recognition. These biometric traits offer many advantages over knowledge and possession-based approaches. For instance, palmprint images have rich, unique features for reliable human identification, and they have received significant research attention due to their stability, reliability, and uniqueness, which makes them a competitive area of research. This paper provides a mini overview of contactless palmprint recognition systems as well as preliminary findings. The various types of Region of Interest (ROI) extraction algorithms, feature extraction, and matching algorithms are well discussed. In addition, the state-of-the-art performance of existing works is presented.
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2 June 2023
ADVANCES IN INTELLIGENT APPLICATIONS AND INNOVATIVE APPROACH
3–5 March 2022
Jaipur, India
Research Article|
June 02 2023
Contactless palmprint recognition: A mini review
Alausa Dele Wasiu;
Alausa Dele Wasiu
a)
1
Department of Electrical and Information Engineering, Covenant University
, Ota, Nigeria
a)Corresponding author: [email protected]
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Emmanuel Adetiba;
Emmanuel Adetiba
b)
1
Department of Electrical and Information Engineering, Covenant University
, Ota, Nigeria
2
Covenant Applied Informatics and Communication Africa Center of Excellence, Covenant University
, Ota, Nigeria
3
HRA, Institute for Systems Science, Durban University of Technology
, Durban, South Africa
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Joke A. Badejo;
Joke A. Badejo
c)
1
Department of Electrical and Information Engineering, Covenant University
, Ota, Nigeria
2
Covenant Applied Informatics and Communication Africa Center of Excellence, Covenant University
, Ota, Nigeria
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Obiseye Obiyemi;
Obiseye Obiyemi
d)
4
KZN e-Skills CoLab, Durban University of Technology
, Durban, South Africa
5
Department of Electrical and Electronic Engineering, Osun State University
, Osogbo, Africa Nigeria
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Surendra Thakur;
Surendra Thakur
e)
4
KZN e-Skills CoLab, Durban University of Technology
, Durban, South Africa
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Oluwadamilola Oshin
Oluwadamilola Oshin
f)
1
Department of Electrical and Information Engineering, Covenant University
, Ota, Nigeria
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a)Corresponding author: [email protected]
AIP Conf. Proc. 2760, 020005 (2023)
Citation
Alausa Dele Wasiu, Emmanuel Adetiba, Joke A. Badejo, Obiseye Obiyemi, Surendra Thakur, Oluwadamilola Oshin; Contactless palmprint recognition: A mini review. AIP Conf. Proc. 2 June 2023; 2760 (1): 020005. https://doi.org/10.1063/5.0149085
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