Contactless Palmprint Recognition for Children
dc.contributor.author | Akash M Godbole, Steven A Grosz | |
dc.contributor.editor | Damer, Naser | |
dc.contributor.editor | Gomez-Barrero, Marta | |
dc.contributor.editor | Raja, Kiran | |
dc.contributor.editor | Rathgeb, Christian | |
dc.contributor.editor | Sequeira, Ana F. | |
dc.contributor.editor | Todisco, Massimiliano | |
dc.contributor.editor | Uhl, Andreas | |
dc.date.accessioned | 2023-12-12T10:46:46Z | |
dc.date.available | 2023-12-12T10:46:46Z | |
dc.date.issued | 2023 | |
dc.description.abstract | Effective distribution of nutritional and healthcare aid for children, particularly infants and toddlers, in the world’s least developed and most impoverished countries, is a major problem due to lack of reliable identification documents. We present a mobile based contactless palmprint recognition system, Child Palm-ID, which meets the requirements of usability, cost, and accuracy for child recognition. On a contactless child palmprint database, Child-PalmDB1, with 1,020 unique palms (age range of 6 mos. to 48 mos.), Child Palm-ID achieves a TAR=94.8% at FAR=0.1%. Child Palm-ID is also able to recognize adults, achieving a TAR=99.5% on the CASIA contactless palmprint database and a TAR=100% on the COEP contactless adult palmprint database, both at FAR=0.1%. For child palmprint images captured at an interval of five months with differences in standoff distance, illumination and motion blur, the TAR drops to 80.5% at FAR=0.1%. This indicates that more research remains in contactless child palmprint recognition. | en |
dc.identifier.isbn | 978-3-88579-733-3 | |
dc.identifier.issn | 1617-5468 | |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/43262 | |
dc.language.iso | en | |
dc.pubPlace | Bonn | |
dc.publisher | Gesellschaft für Informatik e.V. | |
dc.relation.ispartof | BIOSIG 2023 | |
dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-339 | |
dc.subject | Periocular | |
dc.subject | Ear | |
dc.subject | Palm | |
dc.subject | and Vein | |
dc.subject | Datasets | |
dc.subject | Evaluation | |
dc.subject | Benchmarking; Mobile-based biometrics | |
dc.title | Contactless Palmprint Recognition for Children | en |
dc.type | Text/Conference Paper | |
mci.conference.date | 20.-22. September 2023 | |
mci.conference.location | Darmstadt | |
mci.conference.sessiontitle | Regular Research Papers | |
mci.reference.pages | 144-155 |
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