Rule-based page segmentation for palm leaf manuscript on color image
© Springer International Publishing AG 2016. Palm leaf manuscripts are important source of history and ancient wisdom. Large number of manuscripts have been already digitized in the form of folio images. To extract useful information, an optical character recognition (OCR) is often considered to be...
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th-cmuir.6653943832-556042018-09-05T03:07:12Z Rule-based page segmentation for palm leaf manuscript on color image Papangkorn Inkeaw Jakramate Bootkrajang Phasit Charoenkwan Sanparith Marukatat Shinn Ying Ho Jeerayut Chaijaruwanich Computer Science Mathematics © Springer International Publishing AG 2016. Palm leaf manuscripts are important source of history and ancient wisdom. Large number of manuscripts have been already digitized in the form of folio images. To extract useful information, an optical character recognition (OCR) is often considered to be the first step towards text mining. Unfortunately, folio images contain multiple unsegmented palm leaf images, making it difficult to manage in OCR process. This motivates us to propose a new page segmentation method for palm leaf manuscripts. This method consists of two main steps, first of which is the detection of objects in folio images using Connected Component Labeling method in a transformed L*a*b* color space. The second step is rule-based selection of objects as either palm leaf or not palm leaf. The experiments performed on 20 publicly available palm leaf manuscripts composed of 384 folio images demonstrated that the proposed method effectively segmented folio images into separate palm leaf images, with 99.86% precision and 96.67% recall scores. 2018-09-05T02:58:22Z 2018-09-05T02:58:22Z 2016-01-01 Book Series 16113349 03029743 2-s2.0-85005952253 10.1007/978-3-319-49304-6_16 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85005952253&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/55604 |
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Computer Science Mathematics Papangkorn Inkeaw Jakramate Bootkrajang Phasit Charoenkwan Sanparith Marukatat Shinn Ying Ho Jeerayut Chaijaruwanich Rule-based page segmentation for palm leaf manuscript on color image |
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© Springer International Publishing AG 2016. Palm leaf manuscripts are important source of history and ancient wisdom. Large number of manuscripts have been already digitized in the form of folio images. To extract useful information, an optical character recognition (OCR) is often considered to be the first step towards text mining. Unfortunately, folio images contain multiple unsegmented palm leaf images, making it difficult to manage in OCR process. This motivates us to propose a new page segmentation method for palm leaf manuscripts. This method consists of two main steps, first of which is the detection of objects in folio images using Connected Component Labeling method in a transformed L*a*b* color space. The second step is rule-based selection of objects as either palm leaf or not palm leaf. The experiments performed on 20 publicly available palm leaf manuscripts composed of 384 folio images demonstrated that the proposed method effectively segmented folio images into separate palm leaf images, with 99.86% precision and 96.67% recall scores. |
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Book Series |
author |
Papangkorn Inkeaw Jakramate Bootkrajang Phasit Charoenkwan Sanparith Marukatat Shinn Ying Ho Jeerayut Chaijaruwanich |
author_facet |
Papangkorn Inkeaw Jakramate Bootkrajang Phasit Charoenkwan Sanparith Marukatat Shinn Ying Ho Jeerayut Chaijaruwanich |
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Papangkorn Inkeaw |
title |
Rule-based page segmentation for palm leaf manuscript on color image |
title_short |
Rule-based page segmentation for palm leaf manuscript on color image |
title_full |
Rule-based page segmentation for palm leaf manuscript on color image |
title_fullStr |
Rule-based page segmentation for palm leaf manuscript on color image |
title_full_unstemmed |
Rule-based page segmentation for palm leaf manuscript on color image |
title_sort |
rule-based page segmentation for palm leaf manuscript on color image |
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2018 |
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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85005952253&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/55604 |
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