On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Development of a Sigma-Lognormal representation for on-line signatures
Pattern Recognition
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This paper presents a signature verification system based on 84 personally selected parameters. An initial set of 300 parameters is first reduced globally by statistical methods. A personalized parameter selection is performed on the reduced parameter set by use of several norms and a linear classifier. The personalized parameter sets of different signers justify that parameter selection should be personalized. Verification results for personalized parameters are given for different norms and compared to results achieved with a function-based system. A method for combining both approaches and the results achieved with this extended system are presented as well.