Synthesis of Common Arabic Handwritings to Aid Optical Character Recognition Research
Identifieur interne : 000005 ( Main/Exploration ); précédent : 000004; suivant : 000006Synthesis of Common Arabic Handwritings to Aid Optical Character Recognition Research
Auteurs : Laslo Dinges ; Ayoub Al-Hamadi ; Moftah Elzobi ; Sherif El-Etriby [Arabie saoudite]Source :
- Sensors (Basel, Switzerland) [ 1424-8220 ] ; 2016.
Abstract
Document analysis tasks such as pattern recognition, word spotting or segmentation, require comprehensive databases for training and validation. Not only variations in writing style but also the used list of words is of importance in the case that training samples should reflect the input of a specific area of application. However, generation of training samples is expensive in the sense of manpower and time, particularly if complete text pages including complex ground truth are required. This is why there is a lack of such databases, especially for Arabic, the second most popular language. However, Arabic handwriting recognition involves different preprocessing, segmentation and recognition methods. Each requires particular ground truth or samples to enable optimal training and validation, which are often not covered by the currently available databases. To overcome this issue, we propose a system that synthesizes Arabic handwritten words and text pages and generates corresponding detailed ground truth. We use these syntheses to validate a new, segmentation based system that recognizes handwritten Arabic words. We found that a modification of an Active Shape Model based character classifiers—that we proposed earlier—improves the word recognition accuracy. Further improvements are achieved, by using a vocabulary of the 50,000 most common Arabic words for error correction.
Url:
DOI: 10.3390/s16030346
PubMed: 26978368
PubMed Central: 4813921
Affiliations:
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Le document en format XML
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Germany;<email>Moftah.Elzobi@ovgu.de</email></nlm:aff></affiliation></author><author><name sortKey="Elzobi, Moftah" sort="Elzobi, Moftah" uniqKey="Elzobi M" first="Moftah" last="Elzobi">Moftah Elzobi</name><affiliation><nlm:aff id="af1-sensors-16-00346">Institute for Information Technology and Communications (IIKT), Otto-von-Guericke-University Magdeburg, D-39016 Magdeburg, Germany;<email>Moftah.Elzobi@ovgu.de</email></nlm:aff></affiliation></author><author><name sortKey="El Etriby, Sherif" sort="El Etriby, Sherif" uniqKey="El Etriby S" first="Sherif" last="El-Etriby">Sherif El-Etriby</name><affiliation><nlm:aff id="af2-sensors-16-00346">Faculty of Computers and Information, Menoufia University-MUFIC, Menoufia 32721, Egypt;<email>sherif.el-etriby@ci.menofia.edu.eg</email></nlm:aff></affiliation><affiliation wicri:level="1"><nlm:aff id="af3-sensors-16-00346">Department of Computer, Umm Al-Qura University, Makkah 21421, Saudi Arabia</nlm:aff><country xml:lang="fr">Arabie saoudite</country><wicri:regionArea>Department of Computer, Umm Al-Qura University, Makkah 21421</wicri:regionArea><wicri:noRegion>Makkah 21421</wicri:noRegion></affiliation></author></analytic><series><title level="j">Sensors (Basel, Switzerland)</title><idno type="eISSN">1424-8220</idno><imprint><date when="2016">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Document analysis tasks such as pattern recognition, word spotting or segmentation, require comprehensive databases for training and validation. Not only variations in writing style but also the used list of words is of importance in the case that training samples should reflect the input of a specific area of application. However, generation of training samples is expensive in the sense of manpower and time, particularly if complete text pages including complex ground truth are required. This is why there is a lack of such databases, especially for Arabic, the second most popular language. However, Arabic handwriting recognition involves different preprocessing, segmentation and recognition methods. Each requires particular ground truth or samples to enable optimal training and validation, which are often not covered by the currently available databases. To overcome this issue, we propose a system that synthesizes Arabic handwritten words and text pages and generates corresponding detailed ground truth. We use these syntheses to validate a new, segmentation based system that recognizes handwritten Arabic words. We found that a modification of an Active Shape Model based character classifiers—that we proposed earlier—improves the word recognition accuracy. Further improvements are achieved, by using a vocabulary of the 50,000 most common Arabic words for error correction.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Maegner, V" uniqKey="Maegner V">V. Maegner</name></author><author><name sortKey="Abed, H E" uniqKey="Abed H">H.E. Abed</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Sajedi, H" uniqKey="Sajedi H">H. Sajedi</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Abdelaziz, I" uniqKey="Abdelaziz I">I. Abdelaziz</name></author><author><name sortKey="Abdou, S" uniqKey="Abdou S">S. Abdou</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Elarian, Y" uniqKey="Elarian Y">Y. 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Elzobi</name></author></analytic></biblStruct></listBibl></div1></back></TEI><affiliations><list><country><li>Arabie saoudite</li></country></list><tree><noCountry><name sortKey="Al Hamadi, Ayoub" sort="Al Hamadi, Ayoub" uniqKey="Al Hamadi A" first="Ayoub" last="Al-Hamadi">Ayoub Al-Hamadi</name><name sortKey="Dinges, Laslo" sort="Dinges, Laslo" uniqKey="Dinges L" first="Laslo" last="Dinges">Laslo Dinges</name><name sortKey="Elzobi, Moftah" sort="Elzobi, Moftah" uniqKey="Elzobi M" first="Moftah" last="Elzobi">Moftah Elzobi</name></noCountry><country name="Arabie saoudite"><noRegion><name sortKey="El Etriby, Sherif" sort="El Etriby, Sherif" uniqKey="El Etriby S" first="Sherif" last="El-Etriby">Sherif El-Etriby</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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