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Offline Signature Verification using FMCN with GA based Optimization of Features

by Yogendra Kumar Jain, Rupal S. Patil
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 53 - Number 2
Year of Publication: 2012
Authors: Yogendra Kumar Jain, Rupal S. Patil
10.5120/8396-2025

Yogendra Kumar Jain, Rupal S. Patil . Offline Signature Verification using FMCN with GA based Optimization of Features. International Journal of Computer Applications. 53, 2 ( September 2012), 33-39. DOI=10.5120/8396-2025

@article{ 10.5120/8396-2025,
author = { Yogendra Kumar Jain, Rupal S. Patil },
title = { Offline Signature Verification using FMCN with GA based Optimization of Features },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 53 },
number = { 2 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 33-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume53/number2/8396-2025/ },
doi = { 10.5120/8396-2025 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:53:07.559459+05:30
%A Yogendra Kumar Jain
%A Rupal S. Patil
%T Offline Signature Verification using FMCN with GA based Optimization of Features
%J International Journal of Computer Applications
%@ 0975-8887
%V 53
%N 2
%P 33-39
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In recent years, along with extraordinary diffusion of internet and growing need of personal identification in many applications, signature verification is considered with interest. This paper proposed an offline signature verification method based on Genetic Algorithm and Fuzzy Min Max Neural Network Classifier with Compensatory Neuron. The proposed method is basically consists of two steps. At first step optimizing the features using genetic algorithm, and at second step signature recognition is done using Fuzzy Min Max Neural Network Classifier with Compensatory Neurons. The sample of signatures is used to represent a particular person. The sample signature is first preprocessed, and then features of the processed signature are extracted by using Krawtchouk moment. After feature extraction, these features are optimized by using genetic algorithm and finally optimized features are given to the classification phase for recognition. With this proposed method, we get the 98% accuracy in recognition and less time is required for classification with optimized features as compared to time required for classification without optimizing feature.

References
  1. Donato Impedovo, and Giuseppe Pirlo, "Automatic Signature Verification: The State of the Art", IEEE Transactions on Systems, Man, and Cybernetics—Part C: Applications and Reviews, Vol. 38, No. 5, September 2008.
  2. Q. Yingyong, B. R. Hunt, "Signature Verification using Global and Grid Features", Pattern Recognition, Vol. 27, No. 12, pp. 1621—1629, Dec. 1994.
  3. J. P. Drouhard, R. Sabourin, and M. Godbout, "A Neural Network Approach to Off-line Signature Verification using Directional PDF", Pattern Recognition, Vol. 29, No. 3, pp. 415-424, March 1996.
  4. G. Rigoll, A. Kosmala, "A Systematic Comparison between On-Line and Off-Line Methods for Signature Verification with Hidden Markov Models", 14th International Conference on Pattern Recognition - Vol II, Australia, pp. 1755-1757, 1998.
  5. M. C. Fairhurst, "Signature Verification Revisited: Promoting Practical Exploitation of Biometric Technology", Inst. Elect. Eng. Electron. Commun. Eng. J. (ECEJ), Vol. 9, No. 6, pp. 273–280, Dec. 1997.
  6. M. C. Fairhurst and E. Kaplani, "Perceptual Analysis of Handwritten Signatures for Biometric Authentication", Inst. Elect. Eng. Proc. Vis. , Image Signal Process. , Vol. 150, No. 6, pp. 389–394, Dec. 2003.
  7. F. Leclerc and R. Plamondon, "Automatic Signature Verification: The State of the Art—1989–1993", Int. J. Pattern Recognit. Artif. Intell. (IJPRAI), Vol. 8, No. 3, pp. 643–660, Jun. 1994.
  8. G. Pirlo, "Algorithms for Signature verification", in Proc. NATO-ASI Series Fundamentals in Handwriting Recognition, S. Impedovo, Ed. Berlin, Germany: Springer-Verlag, , pp. 433–454, 1994.
  9. R. Plamondon and G. Lorette, "Automatic Signature Verification and Writer Identification The state of the art", Pattern Recognition. , Vol. 22, No. 2, pp. 107–131, Jan. 1989.
  10. M. Krawtchouk, "On Interpolation by Means of Orthogonal Polynomials", Memoirs Agricultural Inst. Kyiv, Vol. 4, pp. 21-28, 1929.
  11. P. T. Yap, P. Raveendran, and S. H. Ong, "Krawtchouk Moments as a New Set of Discrete Orthogonal Moments for Image Reconstruction", IJCNN'02, Vol. 1, pp. 908–912, May. 2002.
  12. Anass El affar, Khalid Ferdous, Abdeljabbar Cherkaoui, Hakim El fadili, and Hassan Qjidaal, "Krawtchouk Moment Feature Extraction for Neural Arabic Handwritten Words Recognition", International Journal of Computer Science and Network Security (IJCSNS), Vol. 9, No. 1, pp. 443-448, Jan. 2009.
  13. G. Szego, "Orthogonal Polynomials", American Mathematical Society, Colloquium publication, Vol. 23, 4th Edition, 1975
  14. Q. Ji, and Y. Zhang, "Camera Calibration With Genetic Algorithms", IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, Vol. 31, No. 2, pp. 120-130, March 2001.
  15. V. E. Ramesh and N. Murty, "Off-Line Signature Verification Using Genetically Optimized Weighted Features", Pattern Recognition, Vol. 32, No. 2, pp. 217-233, Feb. 1999.
  16. J. Yang and V. Honavar, "Feature Subset Selection Using a Genetic Algorithm", IEEE Intelligent Systems, Vol. 13, No. 2, pp. 44-49, Apr. 1998.
  17. S. Y. Ho and H. L. Huang. , "Facial Modeling From an Uncalibrated Face Image using a Coarse-To-Fine Genetic Algorithm", Pattern Recognition, Vol. 34, No. 5, pp. 1015-1031, May. 2001.
  18. G. Kim and S. Kim, "Feature Selection Using Genetic Algorithms for Handwritten Character Recognition", 7th IWFHR, pp. 103-112, Sep. 2000.
  19. L. S. Oliveira, N. Benahmed, R. Sabourin, F. Bortolozzi, C. Y. Suen, "Feature Subset Selection Using Genetic Algorithm for Handwritten Digit Recognition", IEEE proceedings of XIV Brazilian Symposium, pp. 362-369, Oct. 2001.
  20. L. Davis. Handbook on Genetic Algorithms. Van Nos-trand Reinhold, 1991.
  21. Abhijeet V. Nandedkar, Prabir K. Biswas, "A Fuzzy Min-Max Neural Network Classifier with Compensatory Neuron Architecture", IEEE transactions on neural networks, Vol. 18, No. 1, pp. 42 -54, Jan. 2007.
  22. F. Bortolozi. E. R. Justino. , A. E. Yocoubi, and R. Sabourin, "An Off-line Signature Verification System Using HMM and Graphometric Features", 4th IAPR International Workshop on Document Analysis Systems, pp. 211-222, 2000.
  23. K. Faez, M. Dehghan, M. Fathi, "Signature Verification Using Shape Descriptor and Multiple Neural Network", Proceedings of IEEE TENCON on Speech and Image Technologies For Computing and Telecommunications, Vol. 1, pp. 415–418, Dec. 1997.
  24. M. Blumenstein, S. Armand, Muthukkumarasamy, "Off-line Signature Verification using the Enhanced Modified Direction Feature and Neural based Classification", International Joint Conference on Neural Networks, pp. 684-691, Oct. 2006.
  25. S. I. Abuhaiba, "Offline Signature Verification Using Graph Matching", Turk J Elec Engine, Vol. 15, No. 1, pp. 89-104, 2007.
  26. S. Reddy, B. Maghi, P. Babu Novel, "Features for Offline Signature Verification", International Journal of Computer, Communication and Control, Vol. 1, pp. 17–24, Jun. 2006.
  27. T. S. Enturk. E. O. Zgunduz. and E. Karshgil, "Offline Signature Verification and Recognition by Support Vector Machine", Proceedings of the 13th European Signal Processing Conference (EUSIPCO), Antalya Turkey, Vol. 4, pp. 2370-2373, Sep. 2005.
  28. D. R. Shashi Kumar, K. B. Raja, R. K Chhotaray, Sabyasachi Pattanaik, "Off-line Signature Verification Based on Fusion of Grid and Global Features Using Neural Networks", International Journal of Engineering Science and Technology Vol. 2, No. 12, pp. 7035-7044. 2010.
  29. Siyuan Chen, and Sargur Srihari, "Use of Exterior Contours and Shape Features in Off-line Signature Verification", Proceedings of the Eighth International Conference on Document Analysis and Recognition ICDAR, Vol. 2, pp. 1280-1284, Sep. 2005.
Index Terms

Computer Science
Information Sciences

Keywords

Signature Verification Krawtchouk Moment Invariant Genetic Algorithm Fuzzy Min Max Neural Network with Compensatory Neuron

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