  In this contribution, a Bayes Ying Yang(BYY) harmony based approach for
on-line signature verification is presented. In the proposed method, a simple
but effective Gaussian Mixture Models(GMMs) is used to represent for each
user's signature model based on the prior information collected. Different from
the early works, in this paper, we use the Bayes Ying Yang machine combined
with the harmony function to achieve Automatic Model Selection(AMS) during the
parameter learning for the GMMs, so that a better approximation of the user
model is assured. Experiments on a database from the First International
Signature Verification Competition(SVC 2004) confirm that this combined
algorithm yields quite satisfactory results.
