loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Jag Mohan Singh ; Ahmad S. Madhun ; Ahmed Mohammed Kedir and Raghavendra Ramachandra

Affiliation: Norwegian Biometrics Laboratory, Norwegian University of Science and Technology, Gjøvik, Norway

Keyword(s): Fingerphotos, Siamese Neural Network, Deep Learning Architecture.

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.219.236.62

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
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; ISSN 2184-4321, SciTePress, pages 553-559. DOI: 10.5220/0010880000003124

@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},
issn={2184-4321},
}

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
IS - 2184-4321
AU - Singh, J.
AU - Madhun, A.
AU - Kedir, A.
AU - Ramachandra, R.
PY - 2022
SP - 553
EP - 559
DO - 10.5220/0010880000003124
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic