Automated Detection of Dyslexia Symptom Based on Handwriting Image for Primary School Children

Automated Detection of Dyslexia Symptom Based on Handwriting Image for Primary School Children

This paper presents an automated detection system to identify the present of dyslexia symptoms in primary school children based on their handwriting images. The proposed automated detection system is developed by using pattern recognition technique. Based on their handwriting images, the pattern rec...

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Bibliographic Details
Main Authors: Balfagih Z. (Author), Halabi W. (Author), Ibrahimi T. (Author), Isa, I.S (Author), Lytras M. (Author), Rambo K. (Author), Ramlan, S.A (Author), Sarirete A. (Author), Sulaiman, S.N (Author), Syazwani Rahimi, W.N (Author), Uddin M. (Author), Visvizi A. (Author)
Format: Article
Language:English
Published: Elsevier B.V. 2019
Subjects:
artificial neural network
Automation
Biological neural systems
Classification accuracy
dyslexia handwriting
Dyslexia symptom
Image processing
Information processing systems
Neural networks
Optical character recognition
Optical character recognition (OCR)
Optical data processing
pattern recognition method
Pattern recognition method
Pattern recognition systems
Pattern recognition techniques
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