Analysis of Finger Vein Recognition using Deep Learning Techniques

Gururaj Harinahalli Lokesh; N. Nydile; Francesco Flammini; K. P. Vidyashree; Soundarya Bidare Chandregowda

doi:10.1145/3529399.3529422

Analysis of Finger Vein Recognition using Deep Learning Techniques

Gururaj Harinahalli Lokesh, N. Nydile, Francesco Flammini, K. P. Vidyashree, Soundarya Bidare Chandregowda

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

In recent years, security has become increasingly important. Because of its resilience, consistent accuracy, and outstanding performance, the Finger Vein Authentication System has piqued our interest. Other kinds of identification, such as fingerprint and iris biometrics, are less reliable. Because finger veins are unique even for identical twins, exist beneath the skin, and remain intact throughout a person's lifetime, finger vein authentication eliminates the danger of alteration. The identification of finger vein patterns has improved significantly using a variety of deep learning approaches. The main goal of this paper is to show different processes of finger vein authentication, as well as the deep learning methods utilized to construct the Finger Vein Recognition system.

Original language	English
Title of host publication	Proceedings of 2022 7th International Conference on Machine Learning Technologies, ICMLT 2022
Publisher	Association for Computing Machinery, Inc
Pages	136-140
Number of pages	5
ISBN (Electronic)	9781450395748
DOIs	https://doi.org/10.1145/3529399.3529422
Publication status	Published - 11-03-2022
Event	7th International Conference on Machine Learning Technologies, ICMLT 2022 - Virtual, Online, Italy Duration: 11-03-2022 → 13-03-2022

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	7th International Conference on Machine Learning Technologies, ICMLT 2022
Country/Territory	Italy
City	Virtual, Online
Period	11-03-22 → 13-03-22

All Science Journal Classification (ASJC) codes

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

Access to Document

10.1145/3529399.3529422

Cite this

Lokesh, G. H., Nydile, N., Flammini, F., Vidyashree, K. P., & Chandregowda, S. B. (2022). Analysis of Finger Vein Recognition using Deep Learning Techniques. In Proceedings of 2022 7th International Conference on Machine Learning Technologies, ICMLT 2022 (pp. 136-140). (ACM International Conference Proceeding Series). Association for Computing Machinery, Inc. https://doi.org/10.1145/3529399.3529422

@inproceedings{5f0fddc2ec7b435f8c2b6e8e1fc6e893,

title = "Analysis of Finger Vein Recognition using Deep Learning Techniques",

abstract = "In recent years, security has become increasingly important. Because of its resilience, consistent accuracy, and outstanding performance, the Finger Vein Authentication System has piqued our interest. Other kinds of identification, such as fingerprint and iris biometrics, are less reliable. Because finger veins are unique even for identical twins, exist beneath the skin, and remain intact throughout a person's lifetime, finger vein authentication eliminates the danger of alteration. The identification of finger vein patterns has improved significantly using a variety of deep learning approaches. The main goal of this paper is to show different processes of finger vein authentication, as well as the deep learning methods utilized to construct the Finger Vein Recognition system.",

author = "Lokesh, {Gururaj Harinahalli} and N. Nydile and Francesco Flammini and Vidyashree, {K. P.} and Chandregowda, {Soundarya Bidare}",

note = "Funding Information: No financial support was received to perform the research work of this manuscript. Publisher Copyright: {\textcopyright} 2022 ACM.; 7th International Conference on Machine Learning Technologies, ICMLT 2022 ; Conference date: 11-03-2022 Through 13-03-2022",

year = "2022",

month = mar,

day = "11",

doi = "10.1145/3529399.3529422",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery, Inc",

pages = "136--140",

booktitle = "Proceedings of 2022 7th International Conference on Machine Learning Technologies, ICMLT 2022",

}

Lokesh, GH, Nydile, N, Flammini, F, Vidyashree, KP & Chandregowda, SB 2022, Analysis of Finger Vein Recognition using Deep Learning Techniques. in Proceedings of 2022 7th International Conference on Machine Learning Technologies, ICMLT 2022. ACM International Conference Proceeding Series, Association for Computing Machinery, Inc, pp. 136-140, 7th International Conference on Machine Learning Technologies, ICMLT 2022, Virtual, Online, Italy, 11-03-22. https://doi.org/10.1145/3529399.3529422

Analysis of Finger Vein Recognition using Deep Learning Techniques. / Lokesh, Gururaj Harinahalli; Nydile, N.; Flammini, Francesco et al.
Proceedings of 2022 7th International Conference on Machine Learning Technologies, ICMLT 2022. Association for Computing Machinery, Inc, 2022. p. 136-140 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Analysis of Finger Vein Recognition using Deep Learning Techniques

AU - Lokesh, Gururaj Harinahalli

AU - Nydile, N.

AU - Flammini, Francesco

AU - Vidyashree, K. P.

AU - Chandregowda, Soundarya Bidare

PY - 2022/3/11

Y1 - 2022/3/11

N2 - In recent years, security has become increasingly important. Because of its resilience, consistent accuracy, and outstanding performance, the Finger Vein Authentication System has piqued our interest. Other kinds of identification, such as fingerprint and iris biometrics, are less reliable. Because finger veins are unique even for identical twins, exist beneath the skin, and remain intact throughout a person's lifetime, finger vein authentication eliminates the danger of alteration. The identification of finger vein patterns has improved significantly using a variety of deep learning approaches. The main goal of this paper is to show different processes of finger vein authentication, as well as the deep learning methods utilized to construct the Finger Vein Recognition system.

AB - In recent years, security has become increasingly important. Because of its resilience, consistent accuracy, and outstanding performance, the Finger Vein Authentication System has piqued our interest. Other kinds of identification, such as fingerprint and iris biometrics, are less reliable. Because finger veins are unique even for identical twins, exist beneath the skin, and remain intact throughout a person's lifetime, finger vein authentication eliminates the danger of alteration. The identification of finger vein patterns has improved significantly using a variety of deep learning approaches. The main goal of this paper is to show different processes of finger vein authentication, as well as the deep learning methods utilized to construct the Finger Vein Recognition system.

UR - http://www.scopus.com/inward/record.url?scp=85132431496&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85132431496&partnerID=8YFLogxK

U2 - 10.1145/3529399.3529422

DO - 10.1145/3529399.3529422

M3 - Conference contribution

AN - SCOPUS:85132431496

T3 - ACM International Conference Proceeding Series

SP - 136

EP - 140

BT - Proceedings of 2022 7th International Conference on Machine Learning Technologies, ICMLT 2022

PB - Association for Computing Machinery, Inc

T2 - 7th International Conference on Machine Learning Technologies, ICMLT 2022

Y2 - 11 March 2022 through 13 March 2022

ER -

Analysis of Finger Vein Recognition using Deep Learning Techniques

Abstract

Publication series

Conference

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this