Off-line signature recognition using morphological pixel variance analysis
Proceedings of the International Conference and Workshop on Emerging Trends in Technology
Signature recognition using vector quantization
Proceedings of the International Conference and Workshop on Emerging Trends in Technology
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This work proposes a method to tackle the problem of detecting skilled forgeries in off-line signature verification. Inspired by the approach adopted by the expert examiner, it is based on a smoothness criterion.From a collection of genuine and skilled forgery signatures, it is observed that although skilled forgery signatures are very similar to genuine ones on a global scale, they are generally less smooth and natural on a detailed scale than the genuine ones, especially for those skilled forgery signatures which consist of cursive graphic patterns. A smoothness index is derived from such signatures. This is combined with other global shape features and used for verification. Satisfactory results are obtained.