Abstract
This chapter introduces a method for off-line verification of signatures. The method can be used to verify signatures and detect skilled forgeries with outstanding performance. It is based on matching the questioned signature with a 3D reference knowledge image (RKI) using ammar matching technique (AMT). The AMT which was developed and modified through years (1989 – 2010) is introduced in detail, and the 3D RKI derived from the methodology of the forensic document examiner (FDE) of working is elaborated. The features extracted using the new knowledge representation method and the AMT has been found to be highly effective in signature verification, and distinctly outperform the classical features like slants, baseline, and contour based ones on the data used. Experimental results of using RKIs built from binary, high pressure, and thinned images for feature extraction and verification are also presented and discussed.
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References
Ammar M, (2003) Application of Artificial Intelligence and Computer Vision Techniques to Signatory Recognition. Pakistan Journal of Information and Technology, 2(1): 44–51
Nagel R N, Rosenfeld A (1997) Computer Detection of Freehand Forgeries. IEEE Transacations on Computers, 26(9): 895–905
Ammar M, Yoshida Y, Fukumura T (1986) A New Effective Approach for Automatic Off-line Verification of Signatures by Using Pressure Features, Proceedings of the 8ICPR, Paris, pp 566–569
Ammar M, Yoshida Y, Fukumura T (1986) Automatic Off-line Verification of Signatures Based on Pressure Features. IEEE Trans on Systems Man and Cybernetics, 16(3): 39–47
Ammar M, Yoshida Y, Fukumura T (1989) Feature Extraction and Selection for simulated Signature Verification, Plamondon R, Suen C Y, Simner M L(eds), Computer Recognition and Human Production of Handwriting(1989), World scientific Publishing, pp 61–76
Ammar M, Yoshida Y, Fukumura T (1989) Off-line Preprocessing and Verification of Signatures. International Journal of Pattern Recognition and Artificial Intelligence, 2(4): 589–602
Ammar M (2002) Method and apparatus for verification of signatures. United States Patent: No 6424728, 07/23/2002.
Deng S P, Liao H Y, Ho C et al (1999) Wavelet-based Off-line Handwritten Signature Verification. Computer Vision Image Understanding, 76: 173–190
Almudena G, et al (2008) Off-line Signature Verification Using Contour Features. In Proceedings, ICFHR, pp 19–21
Alessandro Z, Lee L L. (2003) A Hybrid On/Off Line Handwritten Signature Verification System, Proc 7th 7ICDAR, vol 1: 424–429
Jesus F, Bonilla V, Miguel A et al (2009) Off-line signature Verification Based on Pseudo-Capstral Coefficients. 10th ICDAR, pp 126–130
Larkin L (2009) Off-line Signature Verification, Doctor Thesis, University of Waikato.
Ammar M (1990) Performance of Parametric and Reference Pattern Based Features in Static Signature Verification: A Comparative Study. In IEEE Proceedings of the 10th International Conference on Pattern Recognition. (Atlantic City, New Jersey, USA), IEEEE Computer Society Press, 646–649
Katsuhiko U (2003) Investigation of Off-line Japanese Signatures Verification Using Pattern Matching, 7th ICDAR, vol 2, p 951
Ammar M (1991) Progress in Verification of Skillfully Simulated Handwritten Signatures. International Journal of Pattern Recognition and Artificial Intelligence, 5(1&2): 337–351
Ammar M (1992) Elimination of Skilled Forgeries in Off-line Systems: A Breakthrough, Proceedings, 11ICPR, the Netherlands, pp 415–418, Sept 1992
Sabourin R et al (1997) Off-line Signature Verification by Local Granulometric Size Distributions, PAMI, 19(9): 976–988
Parker J R (2002) Simple Distances Between Handwritten Signatures. Vision Interface, pp 218–223, Calgary, Alberta, 27–29 May 2002
Parker J R (2007) Composite Systems for Handwritten Signature Recognition. In: Yanushkevich S N, Gavrilova M L, Wang P S P (eds) Image Pattern Recognition: Synthesis and Analysis in Biometrics, pp 159–182, WSP
Ammar M (1989) Signature Verification and Description. Doctoral dissertation, Nagoya University, Nagoya, Japan, 1989.
Ammar M (2011) Raising the Performance of Automatic Signature Verification above that Obtainable by the best Feature Set. IJPRAI. IJPRAI, 25(2): 183–206
Ammar M (2010) Using Multisets of Features and Interactive Feature Selection to Get the Best Qualitative Performance for Automatic Signature Verification (this book)
Ammar M (2011) Intelligent Signature Verification and Analysis, Lambert Academic Publishing
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© 2011 Higher Education Press, Beijing and Springer-Verlag Berlin Heidelberg
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Ammar, M. (2011). Off-line Signature Verification by Matching with a 3D Reference Knowledge Image — From Research to Actual Application. In: Wang, P.S.P. (eds) Pattern Recognition, Machine Intelligence and Biometrics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22407-2_26
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DOI: https://doi.org/10.1007/978-3-642-22407-2_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22406-5
Online ISBN: 978-3-642-22407-2
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