This paper investigates the impact of different approximation methods in feature extraction for pattern recognition applications, specifically focused on delta and delta-delta parameters. Using MCYT330 online signature data-base, our experiments show that 11-point approximation outperforms 1-point approximation, resulting in a 1.4% improvement in identification rate, 36.8% reduction in random forgeries and 2.4% reduction in skilled forgeries
@article{arxiv.2406.00512,
title = {On the use of first and second derivative approximations for biometric online signature recognition},
author = {Marcos Faundez-Zanuy and Moises Diaz},
journal= {arXiv preprint arXiv:2406.00512},
year = {2024}
}
Comments
Advances in Computational Intelligence. IWANN 2023. pp 461 to 472