Effectively recognizing broken characters in Historical documents

Historical documents, after being binarized, produce images that contain abundant broken pieces. The presence of these broken pieces naturally complicates the process of OCR and drastically drops the overall recognition accuracy. We propose a highly effective approach to recognize the broken charact...

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Main Authors: Chaivatna Sumetphong, Supachai Tangwongsan
Other Authors: Mahidol University
Format: Conference or Workshop Item
Published: 2018
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Online Access:https://repository.li.mahidol.ac.th/handle/123456789/14031
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spelling th-mahidol.140312018-06-11T11:45:12Z Effectively recognizing broken characters in Historical documents Chaivatna Sumetphong Supachai Tangwongsan Mahidol University Computer Science Historical documents, after being binarized, produce images that contain abundant broken pieces. The presence of these broken pieces naturally complicates the process of OCR and drastically drops the overall recognition accuracy. We propose a highly effective approach to recognize the broken characters using a heuristic enumerative method to find the optimal set partition of the broken pieces. Each subset of the optimal partition is mapped to the best character pattern and the overall image is recognized. Results obtained after performing experiments on a Thai Historical document and an American Historical document are quite promising. Given the generality of the method, it may be applicable to different language scripts given that a properly trained classifier has been developed for that script and font. © 2012 IEEE. 2018-06-11T04:45:12Z 2018-06-11T04:45:12Z 2012-10-09 Conference Paper CSAE 2012 - Proceedings, 2012 IEEE International Conference on Computer Science and Automation Engineering. Vol.3, (2012), 104-108 10.1109/CSAE.2012.6272918 2-s2.0-84867080115 https://repository.li.mahidol.ac.th/handle/123456789/14031 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84867080115&origin=inward
institution Mahidol University
building Mahidol University Library
continent Asia
country Thailand
Thailand
content_provider Mahidol University Library
collection Mahidol University Institutional Repository
topic Computer Science
spellingShingle Computer Science
Chaivatna Sumetphong
Supachai Tangwongsan
Effectively recognizing broken characters in Historical documents
description Historical documents, after being binarized, produce images that contain abundant broken pieces. The presence of these broken pieces naturally complicates the process of OCR and drastically drops the overall recognition accuracy. We propose a highly effective approach to recognize the broken characters using a heuristic enumerative method to find the optimal set partition of the broken pieces. Each subset of the optimal partition is mapped to the best character pattern and the overall image is recognized. Results obtained after performing experiments on a Thai Historical document and an American Historical document are quite promising. Given the generality of the method, it may be applicable to different language scripts given that a properly trained classifier has been developed for that script and font. © 2012 IEEE.
author2 Mahidol University
author_facet Mahidol University
Chaivatna Sumetphong
Supachai Tangwongsan
format Conference or Workshop Item
author Chaivatna Sumetphong
Supachai Tangwongsan
author_sort Chaivatna Sumetphong
title Effectively recognizing broken characters in Historical documents
title_short Effectively recognizing broken characters in Historical documents
title_full Effectively recognizing broken characters in Historical documents
title_fullStr Effectively recognizing broken characters in Historical documents
title_full_unstemmed Effectively recognizing broken characters in Historical documents
title_sort effectively recognizing broken characters in historical documents
publishDate 2018
url https://repository.li.mahidol.ac.th/handle/123456789/14031
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