Printed Arabic Text Recognition using Linear and Nonlinear Regression

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منابع مشابه

Printed Arabic Text Recognition using Linear and Nonlinear Regression

Arabic language is one of the most popular languages in the world. Hundreds of millions of people in many countries around the world speak Arabic as their native speaking. However, due to complexity of Arabic language, recognition of printed and handwritten Arabic text remained untouched for a very long time compared with English and Chinese. Although, in the last few years, significant number ...

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Offline printed Arabic character recognition

........................................................................................................................ i Acknowledgements ...................................................................................................... ii Table of

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Open-vocabulary recognition of machine-printed Arabic text using hidden Markov models

In this paper, we present multi-font printed Arabic text recognition using hidden Markov models (HMMs). We propose a novel approach to the sliding window technique for feature extraction. The size and position of the cells of the sliding window adapt to the writing line of Arabic text and ink-pixel distributions. We employ a two-step approach for mixed-font text recognition, in which the input ...

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Recognition of off-line printed Arabic text using Hidden Markov Models

Using Hidden Markov Models Husni A. Al-Muhtaseb, Sabri A. Mahmoud, Information and Computer Science Department, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia. e-mail: [email protected], [email protected]. and Rami S. Qahwaji Electronic Imaging and media communications department, University of Bradford, Bradford, UK e-mail: [email protected] Abstract Th...

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Segmentation and Recognition of Printed Arabic Characters

Arabic characters differ significantly from other characters such as Latin and Chinese characters in that they are written cursively in both printed and handwritten forms and consist of 28 main characters. However most of their shapes change according to their position in the word. These shapes together with some other secondaries raise the number of classes to 120. Furthermore, some of these c...

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ژورنال

عنوان ژورنال: International Journal of Advanced Computer Science and Applications

سال: 2017

ISSN: 2156-5570,2158-107X

DOI: 10.14569/ijacsa.2017.080129