A survey on Arabic character segmentation

Alginahi, Yasser M.

doi:10.1007/s10032-012-0188-6

Cited by 73 publications

(57 citation statements)

References 79 publications

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“…The Arabic language has unique features that distinguish it from other languages, which have an impact on the development of DIAR applications [10,11]. The main features are:…”

Section: Features Of the Arabic Languagementioning

confidence: 99%

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A Printed PAW Image Database of Arabic Language for Document Analysis and Recognition

Bataineh¹

2017

J. ICT Res. Appl.

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Abstract. Document image analysis and recognition are important topics in the field of artificial intelligence. In this context, the availability of a database with good script samples is an important requirement for machine-learning processes. For Latin and Asian languages many suitable databases exist. However, there is a shortage of databases with Arabic samples. In this work, a new database of printed Arabic text is introduced. The new concept of collecting sub-words (PAWs) instead of words or individual character samples was adopted. These PAWs constitute all words in the Arabic language. The collected database consists of 83,056 images of PAWs extracted from approximately 550,000 different words. Each sample is presented in the database in five font types: Thuluth, Naskh, Andalusi, Typing Machine, and Kufi. In total, the database consists of 415,280 images. Moreover, ground truth information is included with each PAW image to describe its occurrence number, occurrence frequency, positions and the shapes of the characters. This paper presents a statistical analysis of the frequency of each PAW in the Arabic language.

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“…The Arabic language has unique features that distinguish it from other languages, which have an impact on the development of DIAR applications [10,11]. The main features are:…”

Section: Features Of the Arabic Languagementioning

confidence: 99%

“…In addition, there is no central organization to provide a standard reference for the collection and use of Arabic words [10]. Therefore, most of the databases are either very large or extremely small.…”

Section: Database Of Arabic Textsmentioning

confidence: 99%

A Printed PAW Image Database of Arabic Language for Document Analysis and Recognition

Bataineh¹

2017

J. ICT Res. Appl.

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“…(1) Segmentation refers to splitting images, detecting the contour of each word, and classify it into sub-words collected via single processing [9,10]. The second signal views the changes in the system states in sequential order.…”

Section: Classification Pattern Recognition Processes Using Approachesmentioning

confidence: 99%

Efficient Approach to Segment Ligatures and Open Characters in offline Arabic Text

2017

IJCCIE

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Abstract-This paper researches offline Arabic handwriting recognition. It introduces a new approach to segmentation ligature and open Arabic character based on the structural perspective dealing with sub-words/words, including dots to recognize individual letters. Segmentation approaches that have been integrated into the recognition phase have the capability to deal with ligatures and closed characters issues. This complex problem is due to the cursive writing nature of the Arabic language. This paper also develops an Arabic character algorithm on segmented, pixel based and centre reign (CR) to recognize the letters. The evaluation results are stated in the IFN/ENIT and IAM database which indicate the recognition rate and the effectiveness of our system.

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“…The Arabic Alphabet consists of 28 characters and has many characteristics [4]- [5]. Arabic script possesses a cursive text even when printed and the letters are connected from the baseline of the word.…”

Section: Background: Characteristics Of Arabic Scriptsmentioning

confidence: 99%

“…A single character can contain from one to four shapes for each character or ligature, depending on the implementation. The four possible shapes are: isolated; in which case the character is not linked to either the preceding or the following character, final; in which case the character is linked to the preceding character, but not to the following one, initial; in which case the character is linked to the following character but not to the preceding one, and finally, medial; in which case the character is linked to both the preceding and following characters [4]- [5].…”

Section: Background: Characteristics Of Arabic Scriptsmentioning

confidence: 99%

An Enhanced Kashida-Based Watermarking Approach for Increased Protection in Arabic Text-Documents Based on Frequency Recurrence of Characters

Alginahi¹,

Kabir²,

Tayan³

2014

IJCEE

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Abstract:With text being the predominant communication medium on the internet, more attention is required to secure and protect text information. In this work, an invisible watermarking technique based on Kashida-marks is proposed. The watermarking key is predefined whereby a Kashida is placed for a bit 1 and omitted for a bit 0. Kashidas are inserted in the text before a specific list of characters until the entire key is embedded. Two variations to the proposed method were developed, based on the frequency-recurrence properties of the characters. An advantage with the use of frequency recurrence statistics of Arabic characters was evident in this paper since it had enabled the dynamic variation of imperceptibility and robustness levels as required for a target application. The proposed methods proved to achieve the goal of document protection and authenticity with enhanced robustness and improved perceptual similarity with the original cover-text.

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A survey on Arabic character segmentation

Cited by 73 publications

References 79 publications

A Printed PAW Image Database of Arabic Language for Document Analysis and Recognition

A Printed PAW Image Database of Arabic Language for Document Analysis and Recognition

Efficient Approach to Segment Ligatures and Open Characters in offline Arabic Text

An Enhanced Kashida-Based Watermarking Approach for Increased Protection in Arabic Text-Documents Based on Frequency Recurrence of Characters

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