Name
Abstract | ||
|---|---|---|
A new method to select a segment-to-segment matching by analyzing signature verification is presented, accordingly curve segments used in signature verification and the regional feature contained in the curve segment are picked-up and the regional features are selected by GAs. Namely, features selected are first encoded into chromosome, and descendible types are founded by GAs improved locally. A new crossover method is also proposed to determine the number of curve segment. The experiment shows that the algorithms proposed can accurately find optimal features for signature verification and bring the lower FRR and FAR, thereby the veracity in online signature verification is enhanced. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICNC.2008.102 | ICNC |
Keywords | Field | DocType |
lower frr,regional feature,signature verification,optimal feature,new crossover method,online signature verification,curve segment,descendible type,new method,segment-to-segment matching,feature selection,handwriting recognition,databases,manganese,pattern matching,digital signatures,genetic algorithms | Online signature,Distance measurement,Crossover,Pattern recognition,Computer science,Handwriting recognition,Digital signature,Artificial intelligence,Pattern matching,Machine learning,Genetic algorithm | Conference |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mengtian Cui | 1 | 0 | 1.35 |
| Yong Zhong | 2 | 24 | 2.71 |
| Haijun Zhao | 3 | 0 | 0.34 |