The effect of fatigue on the performance of online writer recognition
- URL: http://arxiv.org/abs/2202.12694v1
- Date: Thu, 24 Feb 2022 09:59:32 GMT
- Title: The effect of fatigue on the performance of online writer recognition
- Authors: Enric Sesa-Nogueras, Marcos Faundez-Zanuy, Manuel-Vicente
Garnacho-Casta\~no
- Abstract summary: The performance of biometric modalities based on things done by the subject, like signature and text-based recognition, may be affected by the subject state.
Fatigue is one of the conditions that can significantly affect the outcome of handwriting tasks.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Background: The performance of biometric modalities based on things done by
the subject, like signature and text-based recognition, may be affected by the
subject state. Fatigue is one of the conditions that can significantly affect
the outcome of handwriting tasks. Recent research has already shown that
physical fatigue produces measurable differences in some features extracted
from common writing and drawing tasks. It is important to establish to which
extent physical fatigue contributes to the intra-person variability observed in
these biometric modalities and also to know whether the performance of
recognition methods is affected by fatigue. Goal: In this paper we assess the
impact of fatigue on intra-user variability and on the performance of
signature-based and text-based writer recognition approaches encompassing both
identification and verification. Methods: Several signature and text
recognition methods are considered and applied to samples gathered after
different levels of induced fatigue, measured by metabolic and mechanical
assessment and, also by subjective perception. The recognition methods are
Dynamic Time Warping and Multi Section Vector Quantization, for signatures, and
Allographic Text-Dependent Recognition for text in capital letters. For each
fatigue level, the identification and verification performance of these methods
is measured. Results: Signature shows no statistically significant intra-user
impact, but text does. On the other hand, performance of signature-based
recognition approaches is negatively impacted by fatigue whereas the impact is
not noticeable in text-based recognition, provided long enough sequences are
considered.
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