# Hand Geometry Based Recognition with a MLP Classifier

arXiv: https://arxiv.org/abs/2204.08469 · HTML: https://mlsanity.com/paper/2204.08469/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 21 references that are in the map.
- First posted on arXiv 16 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)

## Abstract (arXiv)

This paper presents a biometric recognition system based on hand geometry. We describe a database specially collected for research purposes, which consists of 50 people and 10 different acquisitions of the right hand. This database can be freely downloaded. In addition, we describe a feature extraction procedure and we obtain experimental results using different classification strategies based on Multi Layer Perceptrons (MLP). We have evaluated identification rates and Detection Cost Function (DCF) values for verification applications. Experimental results reveal up to 100% identification and 0% DCF