Results 121 to 130 of about 4,122 (162)

Arabic text recognition using neural networks

Proceedings of IEEE International Symposium on Circuits and Systems - ISCAS '94, 2002
Recognizing multi-font Arabic texts is a difficult task in the area of optical character recognition (OCR) because Arabic is a cursive type language. This paper proposes a hybrid Arabic character recognition system based on Moment Invariants employing an Artificial Neural Network classifier.
M.M. Altuwaijri, M.A. Bayoumi
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PC based offline Arabic text recognition system

Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings., 2003
Character recognition systems can contribute tremendously to the advancement of automation process and can improve the interaction between man and machine in many applications. In this paper we describe a PC based system for offline recognition of Arabic characters and numerals. The system is based on expressing the machine printed Arabic alpha-numeric
Zidouri, A., Sarfraz, M., Nawaz, S.N., Ahmad, M.J.   +3 more
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Printed Arabic Text Recognition

2012
This chapter addresses automatic printed Arabic text recognition. Arabic text recognition has its own difficulties due to the cursive nature of the scripts, overlapping characters, large number of dots and diacritics, etc. In this chapter, we present a general framework for a printed Arabic text recognition system.
Irfan Ahmed, Sabri A. Mahmoud, Mohammed Tanvir Parvez   +2 more
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Optical character recognition of arabic printed text

2012 IEEE Student Conference on Research and Development (SCOReD), 2012
Optical character recognition (OCR) systems improve human- machine interaction. They are widely used in many areas such as editing and storing previously printed or handwritten documents. Much of research has been done regarding the identification of Latin, Japanese and Chinese characters. However, very little investigation has been performed regarding
Safwa Taha, Yusra Babiker, Mohamed Abbas
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Transfer Learning to improve Arabic handwriting text Recognition

2020 21st International Arab Conference on Information Technology (ACIT), 2020
In recent years, the leveraging of deep learning approaches allows a great progress in text recognition task. But they usually need a considerable amount of training examples to learn a new model. Therefore, lack of data can be an issue when developing a new recognition model, especially for handwriting Arabic text recognition where the lack of ...
Zouhaira Noubigh, Anis Mezghani, Monji Kherallah   +2 more
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Arabic hand-written text recognition

Proceedings ACS/IEEE International Conference on Computer Systems and Applications, 2002
In this paper, I suggest a method to recognize Arabic handwritten text. First, I explain a single-step method for line thinning and introduce the concept of undetermined colour in order to reduce the neighbourhoods, which increases the program speed. Then I discuss the kinds of different critical points which help us in distinguishing one letter from ...
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ARASTI: A database for Arabic scene text recognition

2017 1st International Workshop on Arabic Script Analysis and Recognition (ASAR), 2017
Text in natural scenes provides many information for peoples and presents an essential tool to interact with their environment. Therefore, recognizing text existing in camera-captured images has become an important issue for many researches in the last decades. Currently, there isn't any available dataset of Arabic script text images in the wild. Since
Maroua Tounsi, Ikram Moalla, Adel M. Alimi   +2 more
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Printed Arabic Text Database for Automatic Recognition Systems

Proceedings of the 2019 5th International Conference on Computer and Technology Applications, 2019
Document image analysis and recognition are important topics in artificial intelligence as they are necessary for the retrieval of documents. Hence, the availability of a database with good script samples is a key requirement for machine-learning processes. Good printed text databases exist for Latin languages.
Hassina Bouressace, Janos Csirik
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Multi-phase recognition of multifont photoscript Arabic text

[1990] Proceedings. 10th International Conference on Pattern Recognition, 2002
A new system for the recognition of a multifont photoscript Arabic text is introduced. The distinguishing feature of such text is that it is written cursively. This imposes an additional requirement of isolating each character or set of overlapping characters before recognition. The proposed system is composed of three interleaved phases.
K. El Gowely, O. El Dessouki, A. Nazif
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Survey and bibliography of Arabic optical text recognition

Signal Processing, 1995
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
AlBadr, Badr, Mahmoud, Sabri
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