Hierarchical On-line Arabic Handwriting Recognition

Saabni, Raid; El-Sana, Jihad

doi:10.1109/icdar.2009.263

Cited by 21 publications

(8 citation statements)

References 17 publications

(17 reference statements)

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“…Saabni and Sana performed geometrical processing, i.e. uniform sampling, writing speed normalization by using vertex removal [28] whereas Biadsy et al used low pass filter for smoothing and noise reduction and Douglas and Peucker's algorithm [6] is used for point reduction [5]. Benouareth et al performed smoothing, baseline estimation and thinning operation for offline Arabic handwritten character recognition [21] and Adeed et al performed normalization to reduce the size of the character to uniform height based on its slope, width, and height [8].…”

Section: Related Workmentioning

confidence: 99%

“…Saabni and Sana extracted both global, i.e. loops ascenders, descenders and local features, and local relations between adjacent points whereas the secondary strokes are recognized based on size, location and order [28]. Razzak et al extracted structural features for online Urdu character recognition [27] whereas Hussain et al extracted 20 unique shape defining features from primary stroke [1].…”

Section: Related Workmentioning

confidence: 99%

“…Arabic contains 28 and Persian contains 32 [25]. In other words Urdu script contains all the alphabets used in Arabic and Persian and other additional alphabets to express the Hindi phonemes.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

HMM and fuzzy logic: A hybrid approach for online Urdu script-based languages’ character recognition

Razzak

Anwar

Husain

et al. 2010

Knowledge-Based Systems

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

HMM and fuzzy logic: A hybrid approach for online Urdu script-based languages’ character recognition

Razzak

Anwar

Husain

et al. 2010

Knowledge-Based Systems

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“…Another research done by Saabni and El-Sana [22]. The researchers presented a multi-level recognizer for online Arabic handwriting.…”

Section: Past Work On Online Arabic Handwritingmentioning

confidence: 99%

Feature extraction techniques of online handwriting arabic text recognition

Abuzaraida

Zeki

2013

2013 5th International Conference on Information and Communication Technology for the Muslim World (ICT4M)

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Abstract-Online recognition of Arabic handwritten text has been an ongoing research problem for many years. Generally, online text recognition field has been gaining more interest lately due to the increasing popularity of hand-held computers, digital notebooks and advanced cellular phones. Most of the online text recognition systems consist of three main phases which are preprocessing, feature extraction, and recognition phase. This paper compares between different techniques that have been used to extract the features of Arabic handwriting scripts in online recognition systems. Those techniques attempt to extract the feature vector of Arabic handwritten words, characters, numbers or strokes. This vector then will be fed into the recognition engine to recognize the pattern using the feature vector. The structure and strategy of those reviewed techniques are explained in this article. The strengths and weaknesses of using these techniques will also be discussed.

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“…Another study used this method was done [17] by presenting a multi-level recognizer for online Arabic handwriting. The multi-level recognition is performed through a series of filters that aim to reduce the search space.…”

Section: Past Work On Online Arabic Handwritingmentioning

confidence: 99%

Recognition Techniques for Online Arabic Handwriting Recognition Systems

Abuzaraida

Zeki

2012

2012 International Conference on Advanced Computer Science Applications and Technologies (ACSAT)

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Abstract-Online recognition of Arabic handwritten text has been an on-going research problem for many years. Generally, online text recognition field has been gaining more interest lately due to the increasing popularity of hand-held computers, digital notebooks and advanced cellular phones. However, different techniques have been used to build several online handwritten recognition systems for Arabic text, such as Neural Networks, Hidden Markov Model, Template Matching and others. Most of the researches on online text recognition have divided the recognition system into these three main phases which are preprocessing phase, feature extraction phase and recognition phase which considers as the most important phase and the heart of the whole system. This paper presents and compares techniques that have been used to recognize the Arabic handwriting scripts in online recognition systems. Those techniques attempt to recognize Arabic handwritten words, characters, digits or strokes. The structure and strategy of those reviewed techniques are explained in this article. The strengths and weaknesses of using these techniques will also be discussed.

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Hierarchical On-line Arabic Handwriting Recognition

Abstract: In this paper, we present a multi-level recognizer for online Arabic handwriting. In Arabic script (handwritten and printed)

Cited by 21 publications

References 17 publications

HMM and fuzzy logic: A hybrid approach for online Urdu script-based languages’ character recognition

HMM and fuzzy logic: A hybrid approach for online Urdu script-based languages’ character recognition

Feature extraction techniques of online handwriting arabic text recognition

Recognition Techniques for Online Arabic Handwriting Recognition Systems

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