# Biometric identification by means of hand geometry and a neural net classifier

arXiv: https://arxiv.org/abs/2204.03925 · HTML: https://mlsanity.com/paper/2204.03925/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 12 references that are in the map.
- First posted on arXiv 8 Apr 2022.

## Builds on (most cited first, 4 of 4)

- [Privacy issues on biometric systems](https://mlsanity.com/paper/2202.11415/) (2022)
- [Technological evaluation of two AFIS systems](https://mlsanity.com/paper/2203.00447/) (2022)
- [Biometric recognition: why not massively adopted yet?](https://mlsanity.com/paper/2203.03719/) (2022)
- [Testing report of a fingerprint-based door-opening system](https://mlsanity.com/paper/2202.11419/) (2022)

## Built on by (most cited first, 1 of 1)

- [Biometric verification of humans by means of hand geometry](https://mlsanity.com/paper/2204.07764/) (2022)

## Abstract (arXiv)

This Paper describes a hand geometry biometric identification system. We have acquired a database of 22 people using a conventional document scanner. The experimental section consists of a study about the discrimination capability of different extracted features, and the identification rate using different classifiers based on neural networks.