Modeling Stability in On-line Signatures
A novel definition of stability regions and a new method for detecting them from on-line signatures is introduced in this paper. Building upon handwriting generation and motor control studies, the stability regions is defined as the longest similar sequences of strokes between a pair of genuine signatures. The stability regions are then used to select the most stable signatures, as well as to estimate the extent to which these stability regions are encountered in both genuine and simulated (forged) signatures, thus modeling the signing habit of a subject. Experimental results on the SUSig database show that the proposed model can be effectively used for signature verification.
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