On the use of first and second derivative approximations for biometric online signature recognition
<|reference_start|>On the use of first and second derivative approximations for biometric online signature recognition: 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<|reference_end|>
@article{faundez-zanuy2024on,
    title={On the use of first and second derivative approximations for biometric
  online signature recognition},
    author={Marcos Faundez-Zanuy, Moises Diaz},
    journal={Lecture Notes in Computer Science, vol 14134, 2023},
    year={2024},
    doi={10.1007/978-3-031-43085-5_36},
    archivePrefix={arXiv},
    eprint={2406.00512},
    primaryClass={cs.CV}
}