On handwriting pressure normalization for interoperability of different acquisition stylus
This work addresses interoperability issues in online signature verification systems for biometric security, but it is incremental as it applies known normalization techniques to a specific stylus mismatch scenario.
The paper tackled the problem of biometric recognition accuracy degradation when users switch stylus models with different pressure responses, by proposing a pressure normalization procedure that improved signature identification rates by over 7% in mismatched conditions.
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.