Signature recognition: Difference between revisions
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'''Static:''' In this mode, users write their signature on paper, digitize it through an optical scanner or a camera, and the biometric system recognizes the signature analyzing its shape. This group is also known as “off-line”. |
'''Static:''' In this mode, users write their signature on paper, digitize it through an optical scanner or a camera, and the biometric system recognizes the signature analyzing its shape. This group is also known as “off-line”. |
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'''Dynamic:''' In this mode, users write their signature in a digitizing tablet, which acquires the signature in real time. Another possibility is the acquisition by means of stylus-operated PDAs. Dynamic recognition is also known as “on-line”. The state-of-the-art in signature recognition can be found in the last major international competition<ref>{{cite journal|last=Houmani|first=Nesmaa|coauthors=A. Mayoue, S. Garcia-Salicetti, B. Dorizzi, M.I. Khalil, M. Mostafa, H. Abbas, Z.T. Kardkovàcs, D. Muramatsu, B. Yanikoglu, A. Kholmatov, M. Martinez-Diaz, J. Fierrez, J. Ortega-Garcia, J. Roure Alcobé, J. Fabregas, M. Faundez-Zany, J. M. Pascual-Gaspar, V. Cardeñoso-Payo, C. Vivaracho-Pascual|title=BioSecure signature evaluation campaign (BSEC'2009): Evaluating online signature algorithms depending on the quality of signatures|journal=Pattern Recognition|year=2012|month=March|volume=45|issue=3|pages=993-1003|url=http://www.sciencedirect.com/science/article/pii/S0031320311003220}}</ref> |
'''Dynamic:''' In this mode, users write their signature in a digitizing tablet, which acquires the signature in real time. Another possibility is the acquisition by means of stylus-operated PDAs. Dynamic recognition is also known as “on-line”. |
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The state-of-the-art in signature recognition can be found in the last major international competition<ref>{{cite journal|last=Houmani|first=Nesmaa|coauthors=A. Mayoue, S. Garcia-Salicetti, B. Dorizzi, M.I. Khalil, M. Mostafa, H. Abbas, Z.T. Kardkovàcs, D. Muramatsu, B. Yanikoglu, A. Kholmatov, M. Martinez-Diaz, J. Fierrez, J. Ortega-Garcia, J. Roure Alcobé, J. Fabregas, M. Faundez-Zany, J. M. Pascual-Gaspar, V. Cardeñoso-Payo, C. Vivaracho-Pascual|title=BioSecure signature evaluation campaign (BSEC'2009): Evaluating online signature algorithms depending on the quality of signatures|journal=Pattern Recognition|year=2012|month=March|volume=45|issue=3|pages=993-1003|url=http://www.sciencedirect.com/science/article/pii/S0031320311003220}}</ref> |
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The most popular [[pattern recognition]] techniques applied for signature recognition are Dynamic Time Warping ([[DTW]]), Hidden Markov Models ([[HMM]]) and Vector Quantization ([[VQ]]). |
The most popular [[pattern recognition]] techniques applied for signature recognition are Dynamic Time Warping ([[DTW]]), Hidden Markov Models ([[HMM]]) and Vector Quantization ([[VQ]]). |
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Revision as of 11:18, 6 August 2012
Signature recognition is a behavioural biometric. It can be operated in two different ways:
Static: In this mode, users write their signature on paper, digitize it through an optical scanner or a camera, and the biometric system recognizes the signature analyzing its shape. This group is also known as “off-line”.
Dynamic: In this mode, users write their signature in a digitizing tablet, which acquires the signature in real time. Another possibility is the acquisition by means of stylus-operated PDAs. Dynamic recognition is also known as “on-line”.
The state-of-the-art in signature recognition can be found in the last major international competition[1]
The most popular pattern recognition techniques applied for signature recognition are Dynamic Time Warping (DTW), Hidden Markov Models (HMM) and Vector Quantization (VQ).
Related techniques
Recently, a handwriten biometric approach has also been proposed[2] . In this case, the user is recognized analyzing his handwriten text.
Databases
Several public databases exist, being the most popular ones SVC[3] , and MCYT[4] .
References
- ^ Houmani, Nesmaa (2012). "BioSecure signature evaluation campaign (BSEC'2009): Evaluating online signature algorithms depending on the quality of signatures". Pattern Recognition. 45 (3): 993–1003.
{{cite journal}}: Unknown parameter|coauthors=ignored (|author=suggested) (help); Unknown parameter|month=ignored (help) - ^ Chapran, J. (2006). "Biometric Writer Identification: Feature Analysis and Classification". International Journal of Pattern Recognition & Artificial Intelligence. 20: 483–503.
- ^ Yeung, D (2004). "SVC2004: First international signature verification competition". Lecture Notes in Computer Science. LNCS-3072: 16–22.
{{cite journal}}: Unknown parameter|coauthors=ignored (|author=suggested) (help) - ^ Ortega-Garcia, Javier. "MCYT Baseline Corpus: A Multimodal Biometric Database". IEE Proceedings - Vision, Image and Signal Processing. 150: 395–401.
{{cite journal}}: Unknown parameter|coauthors=ignored (|author=suggested) (help)