Abstract
The study of human signatures has a long history, but online signature verification is still an active topic in the field of biometrics. This chapter starts with a detailed survey of recent research progress and commercial products, then proposes a typical online dynamic signature verification system based on time-dependent elastic curve matching. Rather than using special dynamic features such as pen pressure and incline, this system uses the 1D curves of signatures which can be captured using a normal tablet. Static and dynamic features can be well extracted from these two curves about x- and y-coordinates and applied to verification. To improve the performance, we introduce into the system different local weight, personal threshold and auto-update algorithms for reference samples. Finally, we present applications of online signature verification for PDAs and in Internet E-commerce.
| Original language | English |
|---|---|
| Title of host publication | Computer-Aided Intelligent Recognition Techniques and Applications |
| Publisher | John Wiley & Sons, Ltd |
| Pages | 99-117 |
| Number of pages | 19 |
| ISBN (Print) | 0470094141, 9780470094143 |
| DOIs | |
| Publication status | Published - 20 Dec 2005 |
Keywords
- Artificial Neural Networks (ANNs)
- Data acquisition
- Dynamic time warping (DTW)
- False Reject Rate or ERR
- Hidden Markov models (HMMs)
- Online signature verification
- Signature Database
- Signature verification system
- Time-dependent elastic curve matching
ASJC Scopus subject areas
- General Engineering