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Offline Signature Recognition using Hidden Markov Model (HMM)

International Journal of Computer Applications
© 2010 by IJCA Journal
Number 2 - Article 4
Year of Publication: 2010
Dr. S. Adebayo Daramola
Prof. T. Samuel Ibiyemi

Dr. Adebayo S Daramola and Prof. Samuel T Ibiyemi. Article:Offline Signature Recognition using Hidden Markov Model (HMM). International Journal of Computer Applications 10(2):17–22, November 2010. Published By Foundation of Computer Science. BibTeX

	author = {Dr. S. Adebayo Daramola and Prof. T. Samuel Ibiyemi},
	title = {Article:Offline Signature Recognition using Hidden Markov Model (HMM)},
	journal = {International Journal of Computer Applications},
	year = {2010},
	volume = {10},
	number = {2},
	pages = {17--22},
	month = {November},
	note = {Published By Foundation of Computer Science}


HMM has been used successfully to model speech and online signature in the past two decades. The success has been attributed to the fact that these biometric traits have time reference. Only few HMM based offline signature recognition systems have be developed because offline signature lack time reference. This paper presents a recognition system for offline signatures using Discrete Cosine Transform (DCT) and Hidden Markov Model (HMM). The signature to be trained or recognized is vertically divided into segments at the centre of gravity using the space reference positions of the pixels. The number of segmented signature blocks is equal to the number of states in the HMM for each user notwithstanding the length of the signatures. Experimental result shows that successful signatures recognition rates of 99.2% is possible. The result is better in comparison with previous related systems based on HMM and statistical classifiers.


  • R. Plamondon and S.N. Srihari. 2000. “On-line and off-line Handwriting Recognition: A comprehensive Survey”, IEE tran. on Pattern Analysis and Machine Intelligence, Vol. 22, no.1, pp. 63-84.
  • F. Leclerc and R. Plamondon. 1994. “Automatic Verification and Writer Identification: The State of the Art 1989-1993”, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 8, pp. 643 – 660.
  • R. Sabourin. 1997. “Off-line signature verification: Recent advances and perspectives”, BSDIA’97, pp.84-98.
  • J. P. Edward. 2002. “Customer Authentication-The Evolution of Signature Verification in Financial Institutions”, Journal of Economic Crime Management, Volume 1, Issue 1.
  • J. Coetzer, B.M. Herbst and J.A. Du Preez. 2004. “Off-line Signature Verification Using the Discrete Radon Transform and a Hidden Markov Model”, Eurasip Journal on Applied Signal Processing - Special Issue on Biometric Signal Processing, Vol. 100, No. 4, pp. 559-571.
  • V. Kiani, R. Pourreza and H. R Pourreza. 2010. “Offline Signature Verification Using Local Radon Transform and Support Vector Machines”, International journal of Image Processing (IJIP) Vol.(3), Issue(5).
  • V.V Kohir and U.B. Desai. 1998. “ Face Recognition Using A DCT-HMM Approach”, Fourth IEEE workshop on Applications of Computer vision (WACV’98).
  • E. Yacoubi, E.J.R. Justino, R. Sabourin and F. Bortolozzi. 2000. “Off-line signature verification using HMMs and cross-validation”, IEEE International Workshop in Neural Networks for Signal Processing, pp. 859-868.
  • E. Justino, F. Bortolozzi and R. Sabourin. 2001. “Off-line signature verification using HMM for random, simple and skilled forgeries”, Proceedings of Sixth International Conference on Document Analysis and Recognition, Vol. 1, pp. 1031-1034.
  • E. Justino, F. Bortolozzi and R. Sabourin. 2005. “Comparison of SVM and HMM classifiers in the off-line signature verification”, Pattern Recognition Letters, pp. 1377-1385.
  • E. Justino, A. Yacoubi, R. Sabourin and F. Bortolozzi. 2000. “An off-line signature verification system using HMM and graphometric features”, Proc. of the 4th International Workshop on Document Analysis Systems, pp. 211-222.
  • M. Banshider, R .Y Santhosh and B .D Prasanna. 2006. “Novel features for off-line signature verification” International Journal of Computers, Communications & Control ,Vol. 1 , No. 1, pp. 17-24.
  • S. Daramola and S. Ibiyemi. 2010. “Novel Feature Extraction Technique for Offline Signature verification”, International Journal of Engineering Science and Technology, Vol (2)7, pp 3137-3143.
  • S. Daramola and S. Ibiyemi. 2010. “Person Identification System using Static and dynamic Signature Fusion”, International Journal of Computer Science and Information Security, Vol (6)7, pp88-92.
  • L. R. Rabiner. 1989. “A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition,” Proceeding of the IEEE, Vol 77, pp. 257-286.
  • L.R. Rabiner and B.H. Juang. 1993. “Fundamentals of Speech Recognition”, Prentice Hall,