Toe prints: An application study for biometric verification in adults

Syed Sadaf Ali, Vivek Singh Baghel, Iyyakutti Iyappan Ganapathi, Surya Prakash, Ngoc Son Vu, Naoufel Werghi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Biometric recognition systems provide an easy way to verify an individual's identity through physiological and behavioral biometric traits, due to the persistence of these traits. The physiological traits are extensively utilized to secure the applications of numerous fields. Among these, toe print is one of the physiological traits that has been discussed and evaluated for the children; however, it has not been addressed in the past as this can also be utilized to verify the identity of an adult, especially for a person with different abilities. In this paper, we have come up with a feasibility study of toe prints while comparing them with the impression of a person's different fingers in terms of the overall performance of a biometric verification system. To accomplish this task, the toe print database is collected from different persons of age varying from 17 years to 64 years, which is the first database of its kind and is made available in public domain. Fingerprint impressions are also collected along with the toe print to compare the reliability of the toe print with respect to performance using a standard fingerprint verification tool. Verifinger trial version has been utilized by considering the two standard fingerprint verification protocols viz. 1-vs-1 and FVC to assess the performance of the toe print verification system in terms of the equal error rate (EER). The toe print verification system attains 0.04% and 0.01% EER values for 1-vs-1 and FVC protocol, respectively, which clearly depicts the feasibility of toe print as a potential biometric trait.

Original languageBritish English
Title of host publicationProceedings - 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021
PublisherIEEE Computer Society
Pages1418-1424
Number of pages7
ISBN (Electronic)9781665448994
DOIs
StatePublished - Jun 2021
Event2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021 - Virtual, Online, United States
Duration: 19 Jun 202125 Jun 2021

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Conference

Conference2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021
Country/TerritoryUnited States
CityVirtual, Online
Period19/06/2125/06/21

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