ASAR 2021 Online Arabic Writer Identification Competition

Dhieb, Thameur; Boubaker, Houcine; Njah, Sourour; Ayed, Mounir Ben; Alimi, Adel M.

doi:10.1007/978-3-030-86198-8_25

Cited by 4 publications

(1 citation statement)

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“…Indeed, the Beta-elliptical approach and the fuzzy perceptual detector are used for features extraction in various tasks like writer identification [34], [35], signature verification [36], [37] and character recognition [38]. In fact, the Betaelliptical approach is based on a description combining two aspects: 1) Beta functions that characterize the velocity profile in the dynamic domain.…”

Section: Related Workmentioning

confidence: 99%

Parkinson’s Disease Detection From Online Handwriting Based on Beta-Elliptical Approach and Fuzzy Perceptual Detector

Allebawi,

Dhieb,

Neji

et al. 2024

IEEE Access

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The increasing age of our society is connected to a rising number of people suffering from disorders. One such disorder is Parkinson's disease (PD). Predictions indicate that the number of individuals affected by PD will more, than double in the future. Neurologists and data scientists consider handwriting as one of the motor symptoms of PD and recognize it as a valuable resource for detecting this disorder. Within this framework, we introduce an innovative system for Parkinson's disease detection, which encompasses several key stages. The process commences with data augmentation and preprocessing, subsequently leading to the segmentation of online handwriting into Beta strokes. Following that, feature extraction is carried out utilizing the Beta-elliptical approach and the fuzzy perceptual detector. Finally, we employ bidirectional long short-term memory (BLSTM) for the classification task. To assess the performance of our system, we created a new online Arabic handwriting dataset designed for detecting Parkinson's disease. The results we obtained affirm the efficacy of our proposed system. Through comprehensive evaluations conducted on the PaHaW dataset, we achieved good accuracy, thereby highlighting that our system surpasses the performance of existing systems.

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