Segmentation of Arabic Handwritten Documents into Text Lines using Watershed Transform

TitleSegmentation of Arabic Handwritten Documents into Text Lines using Watershed Transform
Publication TypeJournal Article
Year of Publication2017
AuthorsSouhar, A., Y. Boulid, E. Ameur, and M. M. Ouagague
JournalInternational Journal of Interactive Multimedia and Artificial Intelligence
ISSN1989-1660
IssueRegular Issue
Volume4
Number6
Date Published12/2017
Pagination96-102
Abstract

A crucial task in character recognition systems is the segmentation of the document into text lines and especially if it is handwritten. When dealing with non-Latin document such as Arabic, the challenge becomes greater since in addition to the variability of writing, the presence of diacritical points and the high number of ascender and descender characters complicates more the process of the segmentation. To remedy with this complexity and even to make this difficulty an advantage since the focus is on the Arabic language which is semi-cursive in nature, a method based on the Watershed Transform technique is proposed. Tested on «Handwritten Arabic Proximity Datasets» a segmentation rate of 93% for a 95% of matching score is achieved.

KeywordsArabic Documents, Connected Component Analysis, Handwritten Character Recognition, Projection Profile, Text Line Segmentation, Text Mining, Watershed Transform
DOI10.9781/ijimai.2017.08.002
URLhttp://www.ijimai.org/journal/sites/default/files/files/2017/08/ijimai20174_6_13_pdf_11239.pdf
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ijimai20174_6_13.pdf1.28 MB