Analyzing Arabic Handwriting Style through Hand Kinematics

Handwriting style is an important aspect affecting the quality of handwriting. Adhering to one style is crucial for languages that follow cursive orthography and possess multiple handwriting styles, such as Arabic. The majority of available studies analyze Arabic handwriting style from static documents, focusing only on pure styles. In this study, we analyze handwriting samples with mixed styles, pure styles (Ruq'ah and Naskh), and samples without a specific style from dynamic features of the stylus and hand kinematics. We propose a model for classifying handwritten samples into four classes based on adherence to style. The stylus and hand kinematics data were collected from 50 participants who were writing an Arabic text containing all 28 letters and covering most Arabic orthography. The parameter search was conducted to find the best hyperparameters for the model, the optimal sliding window length, and the overlap. The proposed model for style classification achieves an accuracy of 88%. The explainability analysis with Shapley values revealed that hand speed, pressure, and pen slant are among the top 12 important features, with other features contributing nearly equally to style classification. Finally, we explore which features are important for Arabic handwriting style detection.

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Publication Details

Journal
Sensors
Published
2024-09-30
DOI
https://doi.org/10.3390/s24196357
Citations
5
Primary Topic
Handwritten Text Recognition Techniques
Type
article
Field-Weighted Citation Impact
1.25
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article

Analyzing Arabic Handwriting Style through Hand Kinematics

Vahan Babushkin, Mohamad Eid, Muhamed Osman Al-Khalil, Haneen Alsuradi
5 citations
Sensors
Handwritten Text Recognition Techniques
1.25
article

Analyzing Arabic Handwriting Style through Hand Kinematics

Vahan Babushkin, Mohamad Eid, Muhamed Osman Al-Khalil, Haneen Alsuradi
article en
5 citations

Abstract

Handwriting style is an important aspect affecting the quality of handwriting. Adhering to one style is crucial for languages that follow cursive orthography and possess multiple handwriting styles, such as Arabic. The majority of available studies analyze Arabic handwriting style from static documents, focusing only on pure styles. In this study, we analyze handwriting samples with mixed styles, pure styles (Ruq'ah and Naskh), and samples without a specific style from dynamic features of the stylus and hand kinematics. We propose a model for classifying handwritten samples into four classes based on adherence to style. The stylus and hand kinematics data were collected from 50 participants who were writing an Arabic text containing all 28 letters and covering most Arabic orthography. The parameter search was conducted to find the best hyperparameters for the model, the optimal sliding window length, and the overlap. The proposed model for style classification achieves an accuracy of 88%. The explainability analysis with Shapley values revealed that hand speed, pressure, and pen slant are among the top 12 important features, with other features contributing nearly equally to style classification. Finally, we explore which features are important for Arabic handwriting style detection.

SensorsVol. 24(19)
New York University Abu Dhabi (AE), New York University (US)
Quality Education
Openalex Percentile: Top 19%
Handwritten Text Recognition Techniques
1.25
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Analyzing Arabic Handwriting Style through Hand Kinematics — Vahan Babushkin, Mohamad Eid, et al. · Sensors (2024) | TGRS Research Map | TGRS