Multi-expert verification of hand-written signatures

This paper presents a multi-expert system for dynamic signatureverification. The system uses a stroke-oriented description ofsignatures well-suited for multi-expert approach. Each stroke isanalysed in multiple representation domains to verify locallyboth the shape and dynamics of a signature. A two-level schemefor decision combination is used to combine local decisions. Atthe first level soft- and hard- combination rules are used tocombine decisions from different representation domains. At thesecond level simple and weighted averaging is used to combinedecisions from different parts of the signature.

[1]  Réjean Plamondon,et al.  Automatic Signature Verification: The State of the Art - 1989-1993 , 1994, Int. J. Pattern Recognit. Artif. Intell..

[2]  Réjean Plamondon,et al.  Automatic signature verification and writer identification - the state of the art , 1989, Pattern Recognit..

[3]  Réjean Plamondon,et al.  The generation of handwriting with delta-lognormal synergies , 1998, Biological Cybernetics.

[4]  Sebastiano Impedovo,et al.  A Multi-expert System for Dynamic Signature Verification , 2000, Multiple Classifier Systems.

[5]  Marinette Revenu,et al.  A Static Signature Verification System Based on A Cooperating Neural Networks Architecture , 1994, Int. J. Pattern Recognit. Artif. Intell..

[6]  Santanu Chaudhury,et al.  Signature verification using multiple neural classifiers , 1997, Pattern Recognit..

[7]  Mario Vento,et al.  Document validation by signature: a serial multi-expert approach , 1999, Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318).

[8]  G. Dimauro,et al.  A Multi-Expert Signature Verification System for Bankcheck Processing , 1997, Int. J. Pattern Recognit. Artif. Intell..

[9]  Brigitte Wirtz,et al.  Average prototypes for stroke-based signature verification , 1997, Proceedings of the Fourth International Conference on Document Analysis and Recognition.

[10]  Sargur N. Srihari,et al.  On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Y. Sato,et al.  Online Signature Verification Based on Shape, Motion, and Writing Pressure , 1982 .

[12]  Proceedings Seventh International Conference on Document Analysis and Recognition , 2003, Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings..