Dynamic signature pre-processing by modified digital difference analyzer algorithm

Dynamic Signature Recognition is one of the highly accurate biometric traits. We capture live signature of the person hence it is possible to have dynamic characteristics of signature for matching purpose. The signature captured by digitizer hardware is in the form of discreet points; we have observed that because of speed limitations of the hardware we get signature points with small time gap causing loss of information in between two points. Here we propose a system to suppress the loss of point and calculate intermediate point location. We have proposed use of Digital Difference Analyzer (DDA) algorithm with certain modifications for the interpolation of points. This method gives fair reconstruction of dynamic signature with captured multidimensional features.

[1]  Arun Ross,et al.  An introduction to biometric recognition , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

[2]  Jinho Kim,et al.  On-line signature verification using model-guided segmentation and discriminative feature selection for skilled forgeries , 2001, Proceedings of Sixth International Conference on Document Analysis and Recognition.

[3]  Anil K. Jain,et al.  On-line signature verification, , 2002, Pattern Recognit..

[4]  Rafal Doroz,et al.  Method of signature recognition with the use of the mean differences , 2009, Proceedings of the ITI 2009 31st International Conference on Information Technology Interfaces.

[5]  Alessandro Zimmer,et al.  A hybrid on/off line handwritten signature verification system , 2003, Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings..

[6]  D. J. Hamilton,et al.  Low cost dynamic signature verification system , 1995 .

[7]  L. Spaanenburg,et al.  Implementing a DSP Kernel for Online Dynamic Handwritten Signature Verification Using the TMS320 DSP Family , 1995 .

[8]  V. S. Nalwa.  Automatic on-line signature verification , 1997 .

[9]  V A Bharadi,et al.  Signature Recognition using Cluster Based Global Features , 2009, 2009 IEEE International Advance Computing Conference.

[10]  Réjean Plamondon,et al.  The Design of An On-Line Signature Verification System: From Theory to Practice , 1994, Int. J. Pattern Recognit. Artif. Intell..

[11]  Venu Govindaraju,et al.  ER2: an intuitive similarity measure for on-line signature verification , 2004, IWFHR.

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

[13]  Haris Baltzakis,et al.  A new signature verification technique based on a two-stage neural network classifier , 2001 .