Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)

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Multimodal Deep Learning Based Score Level Fusion Using Face and Fingerprint

Authors
Krishna Shinde1, *, Charansing Kayte2
1Department of Computer Science and IT, Dr. B.A.M.U. Aurangabad, Aurangabad, India
2Department of Digital and Cyber Forensic, Government Institute of Forensic Science, Dr. B.A.M.U. Aurangabad, Aurangabad, India
*Corresponding author. Email: shreekriss@gmail.com
Corresponding Author
Krishna Shinde
Available Online 10 August 2023.
DOI
10.2991/978-94-6463-196-8_13How to use a DOI?
Keywords
VGG16; CNN; Deep learning; Score Fusion
Abstract

In the previous decade, biometrics referred to the automatic recognition of persons based on their physiological or behavioural traits but unimodal biometrics have their limitations. Due to its potential to overcome some of the inherent limitations of single biometric modalities while simultaneously enhancing overall recognition rates, multimodal biometrics has recently gained prominence. In this research, we offer a multimodal biometric person authentication system based on pre-train transfer learning VGG16 with CNN and CNN models, that uses the user’s face and fingerprint biometric traits. We have used the own collected samples of same person KVKR face and fingerprint dataset for experimental work. First, we have applied pre-processing data augmentation technique on face and fingerprint data then image enhancement techniques on fingerprint data. In the features extraction, we have extraction the hidden feature of the face and fingerprint images using pre-train VGG16 with CNN and CNN models. The hstack method has been used to combine the features and SoftMax classifier use for features classification. The fusion score is calculated using the fixed-rule-based maximum rule technique, finally we have done comparative analysis of the unimodal and multimodal biometric recognition system.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
Series
Advances in Intelligent Systems Research
Publication Date
10 August 2023
ISBN
978-94-6463-196-8
ISSN
1951-6851
DOI
10.2991/978-94-6463-196-8_13How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Krishna Shinde
AU  - Charansing Kayte
PY  - 2023
DA  - 2023/08/10
TI  - Multimodal Deep Learning Based Score Level Fusion Using Face and Fingerprint
BT  - Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
PB  - Atlantis Press
SP  - 140
EP  - 152
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-196-8_13
DO  - 10.2991/978-94-6463-196-8_13
ID  - Shinde2023
ER  -