# Child Palm-ID: Contactless Palmprint Recognition for Children

arXiv: https://arxiv.org/abs/2305.05161 · HTML: https://mlsanity.com/paper/2305.05161/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 54 references that are in the map.
- First posted on arXiv 9 May 2023.

## Builds on (most cited first, 11 of 11)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [Facial Landmark Detection: a Literature Survey](https://mlsanity.com/paper/1805.05563/) (2018)
- [Learning a Fixed-Length Fingerprint Representation](https://mlsanity.com/paper/1909.09901/) (2019)
- [C2CL: Contact to Contactless Fingerprint Matching](https://mlsanity.com/paper/2104.02811/) (2021)
- [AFR-Net: Attention-Driven Fingerprint Recognition Network](https://mlsanity.com/paper/2211.13897/) (2022)
- [Faster Than Real-time Facial Alignment: A 3D Spatial Transformer Network Approach in Unconstrained Poses](https://mlsanity.com/paper/1707.05653/) (2017)
- [Latent Fingerprint Recognition: Fusion of Local and Global Embeddings](https://mlsanity.com/paper/2304.13800/) (2023)
- [Infant-ID: Fingerprints for Global Good](https://mlsanity.com/paper/2010.03624/) (2020)
- [A Deep Learning based Framework to Detect and Recognize Humans using Contactless Palmprints in the Wild](https://mlsanity.com/paper/1812.11319/) (2018)
- [Learning an Ensemble of Deep Fingerprint Representations](https://mlsanity.com/paper/2209.02425/) (2022)

## Built on by (most cited first, 2 of 2)

- [Mobile Contactless Palmprint Recognition: Use of Multiscale, Multimodel Embeddings](https://mlsanity.com/paper/2401.08111/) (2024)
- [GenPalm: Contactless Palmprint Generation with Diffusion Models](https://mlsanity.com/paper/2406.00287/) (2024)

## Abstract (arXiv)

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%.