Smartphone based Finger-Photo Verification using Siamese Network

Jag Mohan Singh, Ahmad S. Madhun, Ahmed Mohammed Kedir, Raghavendra Ramachandra

2022

Abstract

With the advent of deep-learning, finger-photo verification, a.k.a finger-selfies, is an upcoming research area in biometrics. In this paper, we propose the Siamese Neural Network (SNN) architecture for finger photo verification. Our approach consists of a MaskRCNN network used for finger photo segmentation from an input video frame and the proposed Siamese Neural Network for finger-photo verification. Extensive experiments are carried out on the public dataset consisting of 400000 images extracted from 2000 videos in five different sessions. The dataset has 200 unique fingers, where each finger is captured in 5 sessions, 2 sample videos each with 200 frames. We define protocols for testing in the same session and different sessions with/without using the same subjects replicating the real-world scenario. Our proposed method achieves an EER in the range of 8.9% to 34.7%. Our proposed method does not use COTS and uses only a deep neural network.

Paper Citation

in Harvard Style

Singh J., Madhun A., Kedir A. and Ramachandra R. (2022). Smartphone based Finger-Photo Verification using Siamese Network. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5, SciTePress, pages 553-559. DOI: 10.5220/0010880000003124

in Bibtex Style

@conference{visapp22,
author={Jag Mohan Singh and Ahmad S. Madhun and Ahmed Mohammed Kedir and Raghavendra Ramachandra},
title={Smartphone based Finger-Photo Verification using Siamese Network},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={553-559},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010880000003124},
isbn={978-989-758-555-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - Smartphone based Finger-Photo Verification using Siamese Network
SN - 978-989-758-555-5
AU - Singh J.
AU - Madhun A.
AU - Kedir A.
AU - Ramachandra R.
PY - 2022
SP - 553
EP - 559
DO - 10.5220/0010880000003124
PB - SciTePress