A Hybrid On/Off Line Handwritten Signature Verification System
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
An Efficient Fast Algorithm to Generate Codebook for Vector Quantization
ICETET '08 Proceedings of the 2008 First International Conference on Emerging Trends in Engineering and Technology
Computer Graphics
An introduction to biometric recognition
IEEE Transactions on Circuits and Systems for Video Technology
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Dynamic Signature Recognition is one of the highly accurate biometric traits. We capture live signature of the person hence it is possible to analyze dynamic characteristics of signature for matching purpose. The signature captured by digitizer gives information about dynamic nature of signature and pressure applied while signing. Dynamic parameters such as pressure, X, Y, Z- co-ordinates, Azimuth & Altitude are captured. These signature points are vector in n-dimensional vector space. In this paper we have proposed clustering of these points in vector space to form feature vector is proposed for online signature recognition. For clustering & codebook generation kekre's Vector Quantization Algorithms such as KFCG, KMCG are used with variations. The proposed technique gives up to 97% accuracy.