Recognition of arabic handwritten letters using deep Learning approach
Loading...
Date
2023-06
Journal Title
Journal ISSN
Volume Title
Publisher
MOHAMED BOUDIAF UNIVERSITY - M'SILA
Abstract
Many languages have made significant advancements in the field of character
recognition, including English, Chinese, Japanese, and French, with recognition rates reaching
up to 100% in some cases. However, Arabic handwriting recognition faces lower recognition
rates, primarily due to certain linguistic characteristics that make the recognition process more
challenging, along with a shortage of high-quality available datasets.
Therefore, this memorandum was undertaken with the aim of developing a system for
recognizing handwritten Arabic characters and a word segmentation system. The study began
with an analysis of the Arabic language's structure, followed by an overview of deep neural
network technology, which has proven its efficiency in achieving rapid and reliable recognition
results. Finally, the obtained results were explained and interpreted.
Description
Keywords
recognition of handwritten Arabic letters, segmentation of handwritten Arabic words, convolutional neural networks, processing, Feature extraction, classification