Child Palm-ID: Contactless Palmprint Recognition for Children

TL;DR

This paper introduces Child Palm-ID, a contactless palmprint recognition system designed for children, achieving high accuracy in identifying young children and adults, with implications for aid distribution in developing countries.

Contribution

The paper presents a novel mobile-based contactless palmprint recognition system tailored for children, with a large database and competitive accuracy against state-of-the-art systems.

Findings

Achieves 94.11% TAR at 0.1% FAR on child palmprint database.

Achieves 99.4% TAR on adult palmprint database.

TAR drops to 78.1% for time-separated child palmprints.

Abstract

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%.