An HMM-Based Approach for Off-Line Unconstrained Handwritten Word Modeling and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Signature verification based on a fuzzy genetic algorithm
Knowledge-based intelligent techniques in character recognition
Guide to Biometrics
Using Adapted Levenshtein Distance for On-Line Signature Authentication
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
ER2: An Intuitive Similarity Measure for On-Line Signature Verification
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Handwritten Signature Verification Using Image Invariants and Dynamic Features
CGIV '06 Proceedings of the International Conference on Computer Graphics, Imaging and Visualisation
On-Line Signature Verification by Exploiting Inter-Feature Dependencies
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
The Compact Three Stages Method of the Signature Recognition
CISIM '07 Proceedings of the 6th International Conference on Computer Information Systems and Industrial Management Applications
Off-line signature verification using DTW
Pattern Recognition Letters
Verification of Handwritten Signatures: an Overview
ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
Dynamic signature recognition based on velocity changes of some features
International Journal of Biometrics
The New Method of Signature Recognition Based on Least Squares Contour Alignment
ICBAKE '09 Proceedings of the 2009 International Conference on Biometrics and Kansei Engineering
Hi-index | 0.00 |
In this study, a method of determining the similarity of signatures based on detection of characteristic points was proposed. These points were determined with the use of the IPAN99 algorithm, which detects high curvature points on a contour. A set of such points was treated as characteristic points. Up to now, the IPAN99 algorithm has not been used for finding characteristic points in images of signatures. On the basis of the obtained set of characteristic points, the similarity of signatures was calculated with the use of the ER². This study shows that reducing the number of points with the use of the IPAN99 algorithm allows obtaining a smaller error in signature recognition when compared with an analysis of all points.