On handwriting pressure normalization for interoperability of different acquisition stylus

TL;DR

This paper introduces a pressure normalization method for online handwritten signatures, improving biometric recognition accuracy and enabling stylus interoperability despite different pressure responses.

Contribution

The paper proposes a novel pressure normalization procedure that enhances biometric recognition and allows interoperability across different stylus devices.

Findings

Pressure normalization improves signature identification accuracy by over 7%.

Different stylus devices exhibit varied pressure responses and dynamic ranges.

Normalization reduces performance degradation in mismatched stylus scenarios.

Abstract

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.