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IESK-ArDB: a database for handwritten Arabic and an optimized topological segmentation approach

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Abstract

Even though a lot of researches have been conducted in order to solve the problem of unconstrained handwriting recognition, an effective solution is still a serious challenge. In this article, we address two Arabic handwriting recognition-related issues. Firstly, we present IESK-arDB, a new multi-propose off-line Arabic handwritten database. It is publicly available and contains more than 4,000 word images, each equipped with binary version, thinned version as well as a ground truth information stored in separate XML file. Additionally, it contains around 6,000 character images segmented from the database. A letter frequency analysis showed that the database exhibits letter frequencies similar to that of large corpora of digital text, which proof the database usefulness. Secondly, we proposed a multi-phase segmentation approach that starts by detecting and resolving sub-word overlaps, then hypothesizing a large number of segmentation points that are later reduced by a set of heuristic rules. The proposed approach has been successfully tested on IESK-arDB. The results were very promising, indicating the efficiency of the suggested approach.

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Notes

  1. The second version is planned to be released in July, 2012. It will contain much more samples of word images, 200 full pages of annotated handwritten Arabic text with and without non-text elements, as well as 60 pages of bilingual handwritten Arabic/Latin text. In addition, a software tool for ground truth management will be also made available for download.

  2. Phonemes specific to Farsi are represented by the basic shapes of some letters with additional diacritics, resulting in an alphabet of 32 letters, compared to 28 letters in case of Arabic.

  3. This is due to the fact that Arabic text is written from right to left, and writers usually writing main \(CC\) first then auxiliaries. As a result, auxiliaries are appearing shifted to the right away from their correspondence sub-words.

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Authors and Affiliations

  1. Institute for Electronics, Signal Processing and Communications (IESK), Magdeburg, Germany

    Moftah Elzobi, Ayoub Al-Hamadi & Laslo Dings

  2. Computer Science Department, University of Sharjah, Sharjah, UAE

    Zaher Al Aghbari

Authors
  1. Moftah Elzobi
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  2. Ayoub Al-Hamadi
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  3. Zaher Al Aghbari
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  4. Laslo Dings
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Correspondence to Moftah Elzobi.

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Elzobi, M., Al-Hamadi, A., Al Aghbari, Z. et al. IESK-ArDB: a database for handwritten Arabic and an optimized topological segmentation approach. IJDAR 16, 295–308 (2013). https://doi.org/10.1007/s10032-012-0190-z

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  • DOI: https://doi.org/10.1007/s10032-012-0190-z

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