# On handwriting pressure normalization for interoperability of different acquisition stylus

arXiv: https://arxiv.org/abs/2203.16337 · HTML: https://mlsanity.com/paper/2203.16337/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 29 references that are in the map.
- First posted on arXiv 28 Mar 2022.

## Builds on (most cited first, 1 of 1)

- [Handwriting Biometrics: Applications and Future Trends in e-Security and e-Health](https://mlsanity.com/paper/2202.12760/) (2022)

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

- [On the analysis of saturated pressure to detect fatigue](https://mlsanity.com/paper/2411.04128/) (2024)

## Abstract (arXiv)

In this paper, we present a pressure characterization and normalization procedure for online handwritten acquisition. Normalization process has been tested in biometric recognition experiments (identification and verification) using online signature database MCYT, which consists of the signatures from 330 users. The goal is to analyze the real mismatch scenarios where users are enrolled with one stylus and then, later on, they produce some testing samples using a different stylus model with different pressure response. Experimental results show: 1) a saturation behavior in pressure signal 2) different dynamic ranges in the different stylus studied 3) improved biometric recognition accuracy by means of pressure signal normalization as well as a performance degradation in mismatched conditions 4) interoperability between different stylus can be obtained by means of pressure normalization. Normalization produces an improvement in signature identification rates higher than 7% (absolute value) when compared with mismatched scenarios.