A neural network approach to off-line signature verification using directional PDF

Pattern Recognition

Volumn 29, Issue 3, 1996, Pages 415-424

  Drouhard, Jean Pierre ^a,b   Sabourin, Robert ^a,b   Godbout, Mario ^a  

^a Laboratoire d'Imagerie de Vision et d'Intelligence Artificielle (LIVIA)   (Canada)

^b ÉCOLE DE TECHNOLOGIE SUPÉRIEURE   (Canada)

Author keywords

Automatic signature verification; Backpropagation; Classifiers; Directional probability density function; Neural networks; Pattern recognition

Indexed keywords

AUTOMATION; BACKPROPAGATION; DATABASE SYSTEMS; KNOWLEDGE BASED SYSTEMS; NEURAL NETWORKS; PROBABILITY DENSITY FUNCTION;

AUTOMATIC SIGNATURE VERIFICATION; BACKPROPAGATION NETWORK CLASSIFIER; DIRECTIONAL PROBABILITY DENSITY FUNCTION;

CHARACTER RECOGNITION;

EID: 0030104778     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/0031-3203(95)00092-5     Document Type: Article

References (28)

1. R. Sabourin, Une Approache de Type Compréhension de Scène Appliquée au Problème de la Vérification Automatique de l'Identité par l'Image de la Signature Manuscrite. Ph.D. Thesis, École Polytechnique de Montréal (1990).
2. R. Sabourin, R. Plamondon and G. Lorette, Off-line identification with handwritten signature images: survey and perspectives, Structured Document Image Analysis. H. S. Baird, H. Bunke and K. Yamamoto, eds., pp. 219-234, Springer-Verlag, Germany (1992).
3. W. R. Harrison, Suspect Documents, Their Scientific Examination. Nelson-Hall Publishers, Chicago (1981).
4. G. Poulin, Personal Communicaton, Laboratoire Judicaire de la GRC, 4229 boul. Dorchester ouest, Westmount, QC, H3Z 2T4.
5. R. Sabourin, J.-P. Drouhard, L. Gagné and N. Paquet, Automatic handwritten signature verification using directional PDF and neural networks: a feasibility study, Proc. Conf. Exhibit. Indust. Automat. Montréal, 20. 17-20. 20 (1992).
6. L. Xu, A. Krzyzak and C. Y. Suen, Methods of combining multiple classifiers and their applications to handwriting recognition, IEEE Trans. Syst. Man Cybernet. 22, 418-435 (1992).
7. K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd edn. Academic Press Inc., New York (1990).
8. D. J. Burr, Experiments on neural net recognition of spoken and written text, IEEE Trans. Acoust. Speech Sig. Process. 36, 1162-1168 (1988).
9. D. E. Rumelhart, G. E. Hinton and R. J. Williams, Learning internal representation by error propagation, in Parallel Distributed Processing, D. E. Rumelhart and J. L. McClelland, eds, Vol. 1, pp. 318-362. MIT Press, Massachusetts (1986).
10. R. P. Lippmann, An introduction to computing with neural nets, IEEE ASSP Mag. 4-22 (April 1987).
11. P. D. Wasserman, Neural Computing: Theory and Practice. Van Nostrand Reinhold, New York (1989).
12. R. Hecht-Nielsen, Neurocomputing. Addison-Wesley, New York (1990).
13. J. A. Freeman and D. M. Skapura, Neural Networks: Algorithms, Applications and Programming Techniques. Addison-Wesley, New York (1991).
14. J. Hertz, A Krogh and R. G. Palmer, Introduction to the Theory of Neural Computation. Addison-Wesley, New York (1991).
15. A. J. Maren, D. Jones and F. Franklin, Configuring and optimizing the back-propagation network, Handbook of Neural Computing Applications. Academic Press, Santiago (1990).
16. M. Nadler and E. P. Smith, Pattern Recognition Engineering, John Wiley & Son, New York (1993).
17. B. Dubuisson, Diagnostic et reconnaissance des formes. Hermès, Paris (1990).
18. A. V. Ooyen and B. Neinhuis, Improving the convergence of the backpropagation algorithm, Neural Networks 5, 465-471 (1992).
19. T. P. Vogl, J. K. Mangis, A. K. Rigler, W. T. Zink and D. L. Alkon, Accelerating the convergence of the back propagation method, Biol. Cybernet. 59, 257-263 (1988).
20. R. A. Jacobs, Increased rates of convergence through learning rate adaptation, Neural Networks 1, 295-307 (1988).
21. N. Baba, A new approach for finding the global minimum of error function of neural networks, Neural Networks 2, 367-373 (1989).
22. S. J. Marshall and R. F. Harrison, Optimization and training of the feedforward neural networks by genetic algorithms, 2nd Int. Conf. Artific. Neural Networks 349, 39-43 (1991).
23. S. Akaho and S. Amari, On the capacity of three-layer network, Proc. Int. Joint. Conf. Neural Networks 3, 1-6 (1990).
24. E. B. Baum and D. Haussier, What size net gives valid generalization? Neural Comput. 1, 151-160 (1989).
25. H. Akaike, A new look at the statistical model identification, IEEE Trans. Automat. Control 19, 716-723 (1974).
26. T. Ash, Dynamic node creation in backpropagation networks, Proc. Int. Joint Conf. Neural Networks 2, 623-628 (1989).
27. M. Hagiwara, Novel backpropagation algorithm for reduction of hidden units and acceleration of convergence using artificial selection, Proc. Int. Joint Conf. Neural Networks 2, 625-630 (1990).
28. O. Fujita, Optimisation of the hidden unit function in feedforward neural networks, Neural Networks 5, 755-764 (1992).