Child Palm-ID: Contactless Palmprint Recognition for Children
Akash Godbole Steven A. Grosz Anil K. Jain
Effective distribution of nutritional and healthcare aid for children,
particularly infants and toddlers, in some of the least developed and most
impoverished countries of the world, is a major problem due to the lack of
reliable identification documents. Biometric authentication technology has been
investigated to address child recognition in the absence of reliable ID
documents. We present a mobile-based contactless palmprint recognition system,
called Child Palm-ID, which meets the requirements of usability, hygiene, cost,
and accuracy for child recognition. Using a contactless child palmprint
database, Child-PalmDB1, consisting of 19,158 images from 1,020 unique palms
(in the age range of 6 mos. to 48 mos.), we report a TAR=94.11% @ FAR=0.1%. The
proposed Child Palm-ID system is also able to recognize adults, achieving a
TAR=99.4% on the CASIA contactless palmprint database and a TAR=100% on the
COEP contactless adult palmprint database, both @ FAR=0.1%. These accuracies
are competitive with the SOTA provided by COTS systems. Despite these high
accuracies, we show that the TAR for time-separated child-palmprints is only
78.1% @ FAR=0.1%.