Detection of Text Lines of Handwritten Arabic Manuscripts using Markov Decision Processes

Author
Keywords
Abstract
In a character recognition systems, the segmentation phase is critical since the accuracy of the recognition depend strongly on it. In this paper we present an approach based on Markov Decision Processes to extract text lines from binary images of Arabic handwritten documents. The proposed approach detects the connected components belonging to the same line by making use of knowledge about features and arrangement of those components. The initial results show that the system is promising for extracting Arabic handwritten lines.
Year of Publication
2016
Journal
International Journal of Interactive Multimedia and Artificial Intelligence
Volume
4
Issue
Special Issue on Artificial Intelligence Underpinning
Number
1
Number of Pages
31-36
Date Published
09/2016
ISSN Number
1989-1660
Citation Key
URL
http://www.ijimai.org/JOURNAL/sites/default/files/files/2016/02/ijimai20164_1_6_pdf_34205.pdf
DOI
10.9781/ijimai.2016.416
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