Patent ID: 6157731
Filing Date: 2000-12-05
Classification: G06K

Abstract:
A method for processing a set of at least two training signatures provided by a person, leading to a stored model of the class of signatures made by said person, the method comprising, for each said signature:receiving a digitally sampled signature signal and storing it as a raw signature;smoothing and normalizing the raw signature and storing the result as a preprocessed signature;dividing the pre-processed signature into segments;evaluating at least one observable on each said segment, thereby to obtain a respective feature value; andmapping each segment to a particular state of a hidden Markov model according to a rule, wherein:the rule tends to maximize the likelihood that the respective feature values were generated by a sequence of states defined by said mapping, andthere are more segments than there are states, so that each signature will have more than unit duration in at least some states;the method further comprising:storing, as part of said model, a statistical distribution over the training signatures of the feature values corresponding to at least one said observable;CHARACTERIZED IN THATthe method further comprises:storing as part of said model, a statistical distribution over the training signatures of the duration in each of the states.