2009 International Symposium on Intelligent Ubiquitous Computing and Education, 2009, p.202-205
2009
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- Autor(en) / Beteiligte
- Titel
- On-line Handwritten Signature Verification Based on Two Levels Back Propagation Neural Network
- Ist Teil von
- 2009 International Symposium on Intelligent Ubiquitous Computing and Education, 2009, p.202-205
- Ort / Verlag
- IEEE
- Erscheinungsjahr
- 2009
- Quelle
- IEEE Electronic Library Online
- Beschreibungen/Notizen
- A new algorithm for on-line handwriting signature verification is proposed. 15 statistic features is used for representing the signature, which extracted from the handwritten signature, at the same time, applied as the input of Back Propagation Neural Network. Via the Daubechies-6 wavelet transforming, 32 wavelet decomposition coefficients of X coordinate and Y coordinate are selected as wavelet features. The two levels verification method is considered. The first level adopts statistic features, and wavelet features as the second. Through verifying five groups signature, FRR (False Rejection Rate) of the whole samples verification arrives at 6%, and FAR (False Acceptance Rate) is 1.07%. The experimental results show the efficiency and feasibility of this algorithm.
- Sprache
- Englisch
- Identifikatoren
- ISBN: 9780769536194, 0769536190DOI: 10.1109/IUCE.2009.142Titel-ID: cdi_ieee_primary_5223210
- Format
- –
- Schlagworte
- Back Propagation Neural Network, Costs, Feature extraction, Forgery, Handwriting recognition, Hidden Markov models, Intelligent networks, momentum item method, Neural networks, On-line Handwritten sigature verification, Robustness, Spatial databases, Statistics, wavelet decomposition