Arabic Handwritten Letters Recognition
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Date
2022-06-10
Journal Title
Journal ISSN
Volume Title
Publisher
UNIVERSITY of M'SILA
Abstract
The main goal of our work is to exploit the effectiveness of artificial intelligence methods
to recognize handwritten Arabic letters. In this work, for the dataset, we use the AHCD
dataset to train and test the Random Forest model. We rely on two different approaches to
recognize the letter. In the first one, the model takes as inputs 16 features extracted from
the image, whereas in the second approach, the model takes the whole image as an input.
We use Python as the programming language. We achieved a training accuracy of 97.14%
and a testing accuracy of 73.48%.
Description
Keywords
Artificial Intelligence, Random Forest, feature extraction, recognize handwritten Arabic letters, Python.