Name
Abstract | ||
|---|---|---|
In this paper, we propose a new signature verification method. Parameters of the on-line signature Eire decomposed into multi-level signals by utilizing the DWT (discrete wavelet transform). Personal features are emphasized by the DWT sub-band decomposition and extracted. The extracted features are verified using the adaptive algorithm. On-line signature is subtly various comparing with other biometrics, therefore, there is fluctuation in the number of strokes. Then, we also propose a method which is robust to fluctuation of the number of strokes by using the DP (dynamic programming) matching. Through computer simulations, the effectiveness of these proposed methods is confirmed. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/ISCAS.2003.1205776 | ISCAS |
Keywords | Field | DocType |
adaptive signal processing,discrete wavelet transforms,dynamic programming,feature extraction,handwriting recognition,pattern matching,DWT based feature extraction,DWT sub-band decomposition,adaptive algorithm,discrete wavelet transform,dynamic programming matching,multilevel signals,online signature verification method,stroke fluctuation | Dynamic programming,Pattern recognition,Computer science,Handwriting recognition,Feature extraction,Adaptive filter,Discrete wavelet transform,Artificial intelligence,Biometrics,Adaptive algorithm,Pattern matching | Conference |
Volume | Citations | PageRank |
4 | 8 | 0.93 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Isao Nakanishi | 1 | 104 | 28.15 |
| Naoto Nishiguchi | 2 | 21 | 2.73 |
| Yoshio Itoh | 3 | 59 | 18.04 |
| Yutaka Fukui | 4 | 55 | 12.83 |