CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Performance Considerations in Implementing Offline Signature Verification System

by Charu Jain, Priti Singh, Aarti Chugh
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 46 - Number 11
Year of Publication: 2012
Authors: Charu Jain, Priti Singh, Aarti Chugh
10.5120/6950-9223

Charu Jain, Priti Singh, Aarti Chugh . Performance Considerations in Implementing Offline Signature Verification System. International Journal of Computer Applications. 46, 11 ( May 2012), 1-4. DOI=10.5120/6950-9223

@article{ 10.5120/6950-9223,
author = { Charu Jain, Priti Singh, Aarti Chugh },
title = { Performance Considerations in Implementing Offline Signature Verification System },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 46 },
number = { 11 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume46/number11/6950-9223/ },
doi = { 10.5120/6950-9223 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:39:26.590862+05:30
%A Charu Jain
%A Priti Singh
%A Aarti Chugh
%T Performance Considerations in Implementing Offline Signature Verification System
%J International Journal of Computer Applications
%@ 0975-8887
%V 46
%N 11
%P 1-4
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Handwritten signatures are widely accepted as a means of document authentication, authorization and personal verification. In modern society where fraud is rampant, there is the need for an automatic Handwritten Signature Verification (HSV) system to complement visual verification. An implementation is a realization of a technical specification or algorithm as a program, software component, or other computer system through programming and deployment. Many approaches are possible to the implementation of a signature verification system [1, 2]. This paper highlights the key performance considerations when planning the implementation of a signature verification system.

References
  1. Plamondon, R. and Lorette, G. : Automatic signature verification and writer identification: the state of the art, Pattern Recognition, 22, 1 07- 13 1, 1989
  2. Leclerc, F. and Plamondon, R. : Automatic signature verification - the state of the art 1989-1993, Int. J. Patt. Rec. & Art. Int. , 8,643-659, 1994.
  3. H B kekre, V A Bharadi, "Specialized Global Features for Off-line Signature Recognition", 7th Annual National Conference on Biometrics RFID and Emerging Technologies for Automatic Identification, VPM Polytechnic, Thane, January 2009.
  4. H B Kekre, V A Bharadi, "Signature Recognition using Cluster Based Global Features", IEEE International Conference (IACC 2009), Thapar University, Patiala- Punjab, India. March 2009,
  5. H. Baltzakis, N. Papamarkos, "A new signature verification technique based on a two-stage neural network classifier", Engineering Applications of Artificial Intelligence 14 (2001).
  6. Almudena Gilperez, Fernando Alonso-Fernandez, Susana Pecharroman, Julian Fierrez, Javier Ortega-Garcia, "Off-line Signature Verification Using Contour Features", Biometric Recognition Group – ATVS, 2008.
  7. Martinez L. E. , Travieso C. M. , Alonso J. B. , Ferrer M. A. , Parametrization of a Forgery handwritten signature verification system using SVM, IEEE, vol. 2, no. 3, pp. 193_196, 2004.
  8. Cajote R. D. , Guevara, R. C. L. , Global word shape processing using polarradii graphs for off-line handwriting recognition, IEEE, no. 7, 2004.
  9. Miguel A. Ferrer, Jesu´s B. Alonso, and Carlos M. Travieso. : Offline Geometric Parameters for Automatic Signature Verification Using Fixed- Point Arithmetic. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 6, June 2005 p 993-997.
  10. Robert Sabourin, J. -P. Drouhard, Etienne Sum Wah: Shape Matrices as a Mixed Shape Factor for Off-line Signature Verification. Fourth International Conference Document Analysis and Recognition (ICDAR'97), pp. 661.
  11. H. A. Sofien Touj, Najoua Ben Amara, Global feature extraction of offline arabic handwriting, IEEE SMC, vol. 2, no. 4, 2003.
  12. Jalal Mahmud and Chowdhury Mofizur Rahman: On the Power of Feature Analyzer for Signature Verification. Proceedings of the Digital Imaging Computing: Techniques and Applications (DICTA 2005).
  13. Bence K?vári: The Development of Off-Line Signature Verification Methods, Comparative Study. Proceedings of microCAD, International Scientific Conference, 2007
  14. Camino J. L. , Travieso C. M. , Morales C. R. , Ferrer M. A. , Signature classification by Hidden Markov model, IEEE, no. 5, 1999.
  15. Jinhong K. Guo, David Doermann, Azriel Rosenfeld: Off-Line Skilled Forgery Detection Using Stroke and Sub-stroke Properties. Proceedings of the International Conference on Pattern Recognition (ICPR'00)
  16. A. El-Yacoubi, M. Gilloux, R. Sabourin, C. y. Suen, An HMM-based approach for off-line unconstrained handwritten word modeling and recognition, IEEE, no. 6, 1999.
  17. Stephane Armand, Michael Blumenstein and Vallipuram Muthukkumarasamy: Off-line Signature Verification Based on the Modified Direction Feature. The 18th International Conference on Pattern Recognition (ICPR'06), 2006.
  18. Charu Jain, Priti Singh, Aarti Chugh: Panoramic View of Offline Signature Verification: A Survey . Proceedings of the National Conference on Convergence of Emerging Technologies, 2011.
  19. R. Sabourin, G. Genest, F. J. Preteux, "Off-line signature verification local granulometric size distributions", IEEE Trans. Pattern Anal. Mach. Intell. 19 (9) (1997) 976-988.
  20. Bai-ling Zhang, "Off-line Signature Recognition and Verification by Kernel Principal Component Self regression", (ICMLA'06), 0- 7695-2735-3/06, 2006, 4 – 6.
  21. H. Baltzakis, N. Papamarkos, "A new signature verification technique based on a two-stage neural network classifier", Engineering Applications of Artificial Intelligence 14 (2001) 95±103.
  22. J Edson, R. Justino, F. Bortolozzi and R. Sabourin, "The Interpersonal and Intrapersonal Variability Influences on Off-line Signature Verification Using HMM", Proc. XV Brazilian Symp. Computer Graphics and Image Processing, 2002, pp. 197-202,Oct. 2002.
  23. B. Fang, C. H. Leung, Y. Y. Tang, P. C. K. Kwok, K. W. Tse, Y. K. Wong, "Offline signature verification with generated training samples", IEEE Proc, Image Signal Process. 149 (2) (2002) 85-90.
  24. Miguel A. Ferrer, Jesu´s, B. Alonso, and Carlos M. Travieso, "Offline Geometric Parameters for Automatic Signature Verification Using Fixed-Point Arithmetic", IEEE transactions on pattern analysis and machine intelligence, vol. 27, no. 6, June 2005
  25. S. Pinge, H. Kekre, " Signature Identification using Neural Networks", Proceedings of National Conference on Image Processing 2005 (NCIP2005), Organized by TSEC, Mumbai, pp 31-39
  26. Charu Jain, Priti Singh, Aarti Chugh: An Optimal Approach to Offline Signature Verification System using GMM, Proceedings of International Conference on Science and Engineering (ICSE 2011).
  27. Yazan M. Al-Omari, Siti Norul Huda Sheikh, Khairuddin," State-of-the art in offline verification system", Proceedings of International Conference on Pattern Analysis and Intelligent Robotics, June 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Handwritten Signature Verification (hsv) Feature Extraction False Rejection Rate (frr)

Powered by PhDFocusTM