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Syllabus Segmentation from Palm Leaf Manuscripts

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dc.contributor.author Soe, Nwe Nwe
dc.contributor.author Htay, Win
dc.date.accessioned 2019-07-04T06:48:13Z
dc.date.available 2019-07-04T06:48:13Z
dc.date.issued 2018-02-22
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/493
dc.description.abstract Historical handwritten palm leaf manuscripts are very informative documents from which we can learn precious and various experiences from them. This paper presents the character segmentations of historical handwriting from palm leaf manuscripts for handwriting character extraction. In this paper an experiment is carried out to choose color array of an image for binarization of palm leaf manuscripts. To extract images of each character from the leaf selected color intensity array is used for binarization by using famous Otsu thresholding algorithm. After that, image is segmented line by line searching optimal points among the lines using object frequency histogram along the line and Otsu algorithm again. These segmented images are the input elements and the character segmentation process as the final stage of this work. The end result is the images array which contains character images of palm leaf manuscripts. These images, the output of this work, can be applied to optical character recognition for text extraction. en_US
dc.language.iso en en_US
dc.publisher Sixteenth International Conferences on Computer Applications(ICCA 2018) en_US
dc.subject palm leaf manuscripts en_US
dc.subject color intensity array en_US
dc.subject syllabus segmentation en_US
dc.subject optimal points en_US
dc.subject line and character segmentation en_US
dc.subject Otsu algorithm en_US
dc.title Syllabus Segmentation from Palm Leaf Manuscripts en_US
dc.type Article en_US


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