CFP last date
01 January 2025
Call for Paper
February Edition
CAE solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 01 January 2025

Submit your paper
Know more
The week's pick
Responsive image
Property (Land) Registration Management Using Blockchain in Nigeria

A. Festus Osuolale Ojebiyi David-Daniel Seriki Oluwasogo
Random Articles
Reseach Article

A Survey on Handwritten Signature Verification Approaches

by Basheer Mohamad Al-Maqaleh, Abdulbaset Mohammed Qaid Musleh
journal cover thumbnail

Communications on Applied Electronics
Foundation of Computer Science (FCS), NY, USA
Volume 4 - Number 8
Year of Publication: 2016
Authors: Basheer Mohamad Al-Maqaleh, Abdulbaset Mohammed Qaid Musleh
10.5120/cae2016652144

Basheer Mohamad Al-Maqaleh, Abdulbaset Mohammed Qaid Musleh . A Survey on Handwritten Signature Verification Approaches. Communications on Applied Electronics. 4, 8 ( April 2016), 23-29. DOI=10.5120/cae2016652144

@article{ 10.5120/cae2016652144,
author = { Basheer Mohamad Al-Maqaleh, Abdulbaset Mohammed Qaid Musleh },
title = { A Survey on Handwritten Signature Verification Approaches },
journal = { Communications on Applied Electronics },
issue_date = { April 2016 },
volume = { 4 },
number = { 8 },
month = { April },
year = { 2016 },
issn = { 2394-4714 },
pages = { 23-29 },
numpages = {9},
url = { https://www.caeaccess.org/archives/volume4/number8/571-2016652144/ },
doi = { 10.5120/cae2016652144 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-09-04T19:54:17.993323+05:30
%A Basheer Mohamad Al-Maqaleh
%A Abdulbaset Mohammed Qaid Musleh
%T A Survey on Handwritten Signature Verification Approaches
%J Communications on Applied Electronics
%@ 2394-4714
%V 4
%N 8
%P 23-29
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The most common secure personal authentication in biometrics is handwritten signature. Signature authentication is the process of verifying an individual’s identity. Signature verification system scan be classified into two methods: online and offline. This paper explains the survey of various approaches related to offline signature verification systems. Further, this paper provides the comparison of those approaches, their results and techniques of feature extraction.

References
  1. Guerbai, Y., Chibani, Y. and Hadjadji, B. 2015. The effective use of the one-class SVM classifier for handwritten signature verification based on writer-independent parameters. Pattern Recognition, vol. 48, pp. 103-113.?
  2. Kumar, P., and Shashwat, K. 2015. A survey on handwritten signature verification techniques. International Journal of Advance Research in Computer Science and Management Studies, vol. 3, Issue 1, pp.182-186.
  3. Bhattacharya, I., Ghosh, P. and Biswas, S. 2013. Offline signature verification using pixel matching technique. Procedia Technology. vol. 10, pp. 970-977.?
  4. Afsardoost, S., Siamak Y., and Mohammad A. K. 2008. Offline signature verification using geometric center features. In Signal Processing International Conference, IEEE (ICSP 2008), pp. 1491-1494.
  5. Daramola, S., and Ibiyemi, S. 2010. Novel feature extraction technique for offline signature verification system. International Journal of Engineering Science and Technology, vol. 2, pp. 3137-3143.?
  6. Ghandali, S. and Moghaddam, M. E. 2009. Offline Persian signature identification and verification based on image registration and fusion. Journal of Multimedia, vol. 4, pp.137-144.?
  7. Vargas, J. F., Ferrer, M., Travieso, C. M., and Alonso, J. B. 2007. Offline handwritten signature GPDS-960 corpus, International Conference on Document Analysis and Recognition (ICDAR), vol. 2, pp. 764-768.
  8. Ferrer, M., Díaz-Cabrera, M., and Morales, A. 2013. Synthetic offline signature image generation. In Proceedings of the 9th International Conference on Biometrics (ICB2013),IEEE, pp. 1-7.?
  9. Batista, L., Granger, E. and Sabourin, R. 2012. Dynamic selection of generative–discriminative ensembles for offline signature verification. Pattern Recognition, vol. 45, pp.1326-1340.?
  10. Kumar, R., Sharma, J. D., and Chanda, B. 2012. Writer independent offline signature verification using surroundedness feature. Pattern Recognition Letters, vol.33, pp. 301-308.
  11. Ferrer, M., Vargas, J., Morales, A., and Ordóñez, A. 2012. Robustness of offline signature verification based on gray level features. IEEE Transactions on Information Forensics and Security,vol. 7, pp. 966-977.?
  12. ZulNarnain, Z., Rahim, M. S. M., Ismail, N. A. F., and Arsad, M. A. M. 2016. Triangular geometric feature for offline signature verification. International Journal of Computer, Electrical, Automation,Control and Information Engineering, vol. 10, pp. 459-462.
  13. Ortega-Garcia, Javier, et al.2003. MCYT baseline corpus: a bimodal biometric database. IEEE Proceedings-Vision, Image and Signal Processing,vol.6, pp.395-401.
  14. Fiérrez-Aguilar, J., Alonso-Hermira, N., MorenoMarquez, G., and Ortega-Garcia, J. 2004. An offline signature verification system based on fusion of local and global information. In Biometric Authentication, pp. 295-306.
  15. Nagendra, B. P., Sagar, K. C., and Reddy, A. S. 2013. Offline signature verification based on GLCM. ? International Journal of Electronics Signals and Systems , vol.3, pp.66-72.
  16. Wai, H., and Soe, L. A. 2014. Offline signature verification system using neural network. International Conference on Advances in Engineering and Technology (ICAET'2014), pp. 302-306.
  17. Ismail, M. A. and Gad, S. 2000. Offline Arabic signature recognition and verification. Pattern Recognition, vol. 33, pp.1727-1740.?
  18. Ahmed, S. M. 2012. Offline Arabic signature verification using geometrical features. National Workshop on Information Assurance Research, Proceedings of (WIAR2012),pp. 1-6.?
  19. Level Otsu, N. 1979. A threshold selection method from gray-level histogram. IEEE Transactions on Systems, Man and Cybernetics, pp. 62-66.?
  20. Srivastava, S., and Agarwal, S. 2013. Offline signature verification based on pixel oriented and component oriented feature extraction. International Journal of Advanced Research in Computer Science, vol. 4, pp.77-83.?
  21. Ramachandra, A. C., Rao, J. S., Raja, K. B., Venugopla, K. R., and Patnaik, L. M. 2009. Robust offline signature verification based on global features. In Advance Computing Conference, IEEE International (IACC 2009), pp. 1173-1178.
  22. Huang, K., and Yan, H. 2002. Offline signature verification using structural feature correspondence. Pattern Recognition, vol.35, pp. 2467-2477.?
  23. Al-Omari, Y. M., Siti Norul H. S. Abdullah, and Omar, K. 2011. State-of-the-art in offline signature verification system. In Pattern Analysis and Intelligent Robotics (ICPAIR2011), International Conference on IEEE, vol. 1, pp. 59-64.
  24. Basheer, M. Al-Maqaleh, and Abdulbaset M. Q.Musleh. 2015. An efficient offline signature verification system using local features. International Journal of Computer Applications, vol.131, no.10, pp. 39-44.?
  25. Abuhaiba, I. S. 2007. Offline signature verification using graph matching. Turk J Elec Engin, vol.15, pp. 89-104.
  26. Majhi, B., Reddy, Y. S., and Babu, D. P. 2006. Novel features for offline signature verification. International Journal of Computers, Communications and Control, vol.1, pp. 17-24.?
  27. Candes, E. J., and Donoho, D. L. 2000. Curvelets: A surprisingly effective nonadaptive representation for objects with edges. Stanford University Ca Dept of Statistics.?
  28. Hetal V.,Davda. and S. K. G. 2014. Offline signature verification system using energy on grid level. International Journal of Engineering Research, vol.3 , pp. 104-107.
  29. Jana, R., Rituparna S., and Debaleena D. 2014. Offline signature verification using Euclidian distance. International Journal of Computer Science and Information Technologies, vol.5, no. 1, pp.707-710.
  30. Roy, S., and Sushila M. 2014. Offline signature verification using grid based and centroid based approach. International Journal of Computer Applications, vol.8, pp. 35-39.
  31. Kaur, R., and Pooja C. 2015. Handwritten signature verification based on surf features using HMM. International Journal of Computer Science Trends and Technology, vol.3,pp.187-195.
  32. Baltzakis, H., and Papamarkos, N. 2001. A new signature verification technique based on a two-stage neural network classifier. Engineering Applications of Artificial intelligence, vol. 14, pp.95-103.?
  33. Suryawanshi, R., Kale, S., Pawar, R., Kadam, S., and Ghule, V. R. 2016. Offline signature cognition and verification using artificial neural network. IJARCCE, vol. 5, pp. 352-354.?
  34. Anjali.R, and Manju R. M. 2013. Offline signature verification based on SVM and neural network. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, pp. 2320–3765.
  35. Singh, P., and Patel, R. 2013. Offline signature verification using fuzzy logic. International Journal of software & Hardware Research in Engineering vol.1, pp.97-101.
  36. Daramola, S. A., and Ibiyemi, T. S. 2010. Offline signature recognition using hidden markov model (HMM). International journal of computer applications, vol.10, pp.17-22.?
  37. Justino, E. J., Bortolozzi, F., and Sabourin, R. 2005. A comparison of SVM and HMM classifiers in the off-line signature verification. Pattern recognition letters, vol.26, pp.1377-1385.?
  38. Pallavi V. H., Salokhe. B. T., and Ashish A. M. 2015. Offline handwritten signature verification using neural network. International Journal Of Innovations In Engineering Research and Technology, vol. 1, pp. 1-5.
  39. Pushpalatha, K. N., and Gautam, A. K. 2014. Offline signature Verification using spatial domain feature sets and support vector machine. International Journal of Emerging Technology and Advanced Engineering, vol.4, Issue 7, pp. 544-551.
Index Terms

Computer Science
Information Sciences

Keywords

Forgery Global Features Local Features Signature Verification.

Powered by PhDFocusTM