Comprehensive synthetic Arabic database for on/off-line script recognition research

Saabni, Raid; El-Sana, Jihad

doi:10.1007/s10032-012-0189-5

Cited by 22 publications

(12 citation statements)

References 23 publications

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“…Except for perturbation-based techniques, the two other techniques require shape-matching operations [14,50]. Table 4 presents different works classified by the three generation-based techniques along with the Rao [42] Guyon [20] Jawahar and Balasubramanian [23] Wang et al [1,21,39] Wang et al [1] Lin et al [53] Choi et al [22,47] Saabni [4,12] Jawahar and Balasubramanian [23] Zheng various output data types used. In the following subsections, each of the three generation techniques is discussed in detail.…”

Section: Generation Techniquesmentioning

confidence: 99%

“…A script can be inherently cursive as in Arabic, inherently discrete as in Hiragana [36] and Katakana [37], or mixed as in modern Latin. Researchers have worked on synthesis of Latin [20,21], Arabic [4,38], Cyrillic [9], Chinese [11,39], Korean (Hangul) [15], Japanese ( [36,40] and [37]), and Indian (Hindi, Tamil, Malayalam, and Telugu) scripts [23]. Occasionally, systems are implemented and tested on multiscripts [2,9,30].…”

Section: Scripts and Languagesmentioning

confidence: 99%

“…Among the refereed journals that contribute to the dissemination of established knowledge in the area are the International Journal of Document Analysis and Recognition (IJDAR) (e.g., [2][3][4]), Pattern Recognition (e.g., [5][6][7][8]), Pattern Recognition Letters (e.g., [9]), Machine Learning (e.g., [10]), and others. Besides, some prestigious conferences such as the International Conference on Document Analysis and Recognition (ICDAR) (e.g., [11][12][13][14]), the International Workshop on Document Analysis Systems (DAS) (e.g., [15]), the International Conference on Pattern Recognition (ICPR) (e.g., [16][17][18][19]), and the International Conference on Frontiers in Handwriting Recognition (ICFHR) (e.g., [20][21][22][23]) help in spreading the advances in the field.…”

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confidence: 99%

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Handwriting synthesis: classifications and techniques

Elarian

Abdel-Aal

Ahmad

et al. 2014

IJDAR

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Handwriting synthesis is the automatic generation of data that resemble natural handwriting. Although handwriting synthesis has recently gained increasing interest, the area still lacks a stand-alone review. This paper provides classifications for the different aspects of handwriting synthesis. It presents the applications, techniques, and evaluation methods for handwriting synthesis based on the several aspects that we identify. Then, it discusses various synthesis techniques. To the best of our knowledge, this paper is the only stand-alone survey on this topic, and we believe it can serve as a useful reference for the researchers in the field of handwriting synthesis.

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Section: Generation Techniquesmentioning

confidence: 99%

Section: Scripts and Languagesmentioning

confidence: 99%

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confidence: 99%

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Handwriting synthesis: classifications and techniques

Elarian

Abdel-Aal

Ahmad

et al. 2014

IJDAR

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“…The only two works, [8] and [24], are about handwriting synthesis using glyph concatenation technique for generating datasets for training handwriting recognition systems, which take Arabic script into account. The current paper to our knowledge is the first article about Farsi/Arabic automatic handwritten font generation.…”

Section: Related Workmentioning

confidence: 99%

Toward automatic development of handwritten personal Farsi/Arabic OpenType $$^{\textregistered }$$ ® fonts

Fouladi

Araabi

2015

IJDAR

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The interest in personalized handwritten fonts has been increased in recent years. This paper concerns with the automatic generation of Farsi/Arabic handwritten fonts. To reach this target, we need to extract the properties of the writer's script style. The "glyphs" (simple characters or ligatures) of the writer's script are extracted from the basic subwords. The basic subwords are acquired from a writer using tabular sheets. A learning method is used in extraction phase. After glyph extraction, four important steps are performed automatically: (a) adjusting glyphs joints and baselines (b) computing metric data, (c) locating dots, and (d) computing kerning pairs. Finally, the gathered information is compiled in an OpenType ® font file structure to generate a computer font, which can be used in any computer application. The results seem visually acceptable.

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“…Providing the query keyword, for word spotting or searching, is usually a challenging task since one should submit a pictorial representation of the keyword. Some approaches manually search for an instance of the keyword within the manuscript [33], while others manually assemble the keyword from the word fragments [30], [32].…”

Section: Introductionmentioning

confidence: 99%

Automatic Synthesis of Historical Arabic Text for Word-Spotting

Kassis

El-Sana

2016

2016 12th IAPR Workshop on Document Analysis Systems (DAS)

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We present a novel framework for automatic and efficient synthesis of historical handwritten Arabic text. The main purpose of this framework is to assist word spotting and keyword searching in handwritten historical documents. The proposed framework consists of two main procedures: building a letter connectivity map and synthesizing words. A letter connectivity map includes multiple instances of the various shape of each letter, since a letter in Arabic usually has multiple shapes depends in its position in the word. Each map represents one writer and encodes the specific handwriting style. The letter connectivity map is used to guide the synthesis of any Arabic continuous subword, word, or sentence. The proposed framework automatically generates the letter connectivity map annotation from a several pages historical pages previously annotated. Once the letter connectivity map is available our framework can synthesis the pictorial representation of any Arabic word or sentence from their text representation. The writing style of the synthesized text resembles the writing style of the input pages. The synthesized words can be used in word-spotting and many other historical document processing applications. The proposed approach provides an intuitive and easy-to-use framework to search for a keyword in the rest of the manuscript. Our experimental study shows that our approach enables accurate results in word spotting algorithms.

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Comprehensive synthetic Arabic database for on/off-line script recognition research

Cited by 22 publications

References 23 publications

Handwriting synthesis: classifications and techniques

Handwriting synthesis: classifications and techniques

Toward automatic development of handwritten personal Farsi/Arabic OpenType $$^{\textregistered }$$ ® fonts

Automatic Synthesis of Historical Arabic Text for Word-Spotting

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