Open AccessRecognition of handwritten Arabic (Indian) numerals using skeleton matching
Author(s) -
Bassam A. Y. Alqaralleh,
Malek Alksasbeh,
Tamer Abukhalil,
Harbi AlMahafzah,
Tawfiq Al Rawashdeh
Publication year - 2020
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v19.i3.pp1461-1468
Subject(s) - arabic numerals , optical character recognition , computer science , character (mathematics) , matching (statistics) , numeral system , artificial intelligence , character recognition , arabic , intelligent word recognition , pattern recognition (psychology) , intelligent character recognition , skeleton (computer programming) , speech recognition , computer vision , image (mathematics) , mathematics , linguistics , statistics , philosophy , geometry , programming language
This paper brings into discussion the problem of recognizing Arabic numbers using a monocular camera as the only sensor. When a digital image is presented in this application, optical character recognition (OCR) can be exploited to comprehend numerical data. However, there has been a limited success when applied to the handwritten Arabic (Indian) numbers. This paper aims to overcome this limitation and introduces optical character recognition system based on skeleton matching. The proposed approach is used for handwritten Arabic numbers only. The experimental results indicate the effectiveness of the proposed optical character recognition system even for numbers written in worst case. The right system achieves a recognition rate of 99.3 %.