#6037. The Effect of Fatigue on the Performance of Online Writer Recognition
July 2026 | publication date |
Proposal available till | 28-05-2025 |
4 total number of authors per manuscript | 0 $ |
The title of the journal is available only for the authors who have already paid for |
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Journal’s subject area: |
Cognitive Neuroscience; |
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Abstract:
The performance of biometric modalities based on things done by the subject, like signature and text-based recognition, may be affected by the subject’s 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. 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. 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.
Keywords:
Fatigue; Online writer recognition; Signature; Signature-based writer recognition; Text-based writer recognition
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