Abstract
In this paper, we show the positive potential of verifying the offline handwritten signatures through discrete Radon transform (DRT), principle component analysis (PCA) and probabilistic neural network (PNN). Satisfactory results are obtained with 1.51%, 3.23%, and 13.07% equal error rate (EER) for random, casual, and skilled forgeries respectively on our independent database.
| Original language | English |
|---|---|
| Title of host publication | 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2010 - In Co-operation with EUROGRAPHICS, Full Papers Proceedings |
| Pages | 31-38 |
| Number of pages | 8 |
| Publication status | Published - 2010 Dec 1 |
| Event | 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2010 - Plzen, Czech Republic Duration: 2010 Feb 1 → 2010 Feb 4 |
Publication series
| Name | 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2010 - In Co-operation with EUROGRAPHICS, Full Papers Proceedings |
|---|
Other
| Other | 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2010 |
|---|---|
| Country | Czech Republic |
| City | Plzen |
| Period | 10/2/1 → 10/2/4 |
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All Science Journal Classification (ASJC) codes
- Computer Graphics and Computer-Aided Design
- Computer Vision and Pattern Recognition
Cite this
}
Offline signature verification through probabilistic neural network. / Yin, Ooi Shih; Teoh, Beng Jin; Yan, Hiew Bee; Han, Pang Ying.
18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2010 - In Co-operation with EUROGRAPHICS, Full Papers Proceedings. 2010. p. 31-38 (18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2010 - In Co-operation with EUROGRAPHICS, Full Papers Proceedings).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Offline signature verification through probabilistic neural network
AU - Yin, Ooi Shih
AU - Teoh, Beng Jin
AU - Yan, Hiew Bee
AU - Han, Pang Ying
PY - 2010/12/1
Y1 - 2010/12/1
N2 - In this paper, we show the positive potential of verifying the offline handwritten signatures through discrete Radon transform (DRT), principle component analysis (PCA) and probabilistic neural network (PNN). Satisfactory results are obtained with 1.51%, 3.23%, and 13.07% equal error rate (EER) for random, casual, and skilled forgeries respectively on our independent database.
AB - In this paper, we show the positive potential of verifying the offline handwritten signatures through discrete Radon transform (DRT), principle component analysis (PCA) and probabilistic neural network (PNN). Satisfactory results are obtained with 1.51%, 3.23%, and 13.07% equal error rate (EER) for random, casual, and skilled forgeries respectively on our independent database.
UR - http://www.scopus.com/inward/record.url?scp=84862080588&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84862080588&partnerID=8YFLogxK
M3 - Conference contribution
SN - 9788086943886
T3 - 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2010 - In Co-operation with EUROGRAPHICS, Full Papers Proceedings
SP - 31
EP - 38
BT - 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, WSCG 2010 - In Co-operation with EUROGRAPHICS, Full Papers Proceedings
ER -