  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.
