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

TitleDetection of Text Lines of Handwritten Arabic Manuscripts using Markov Decision Processes
Publication TypeJournal Article
Year of Publication2016
AuthorsBoulid, Y., A. Souhar, and M. E. Elkettani
JournalInternational Journal of Interactive Multimedia and Artificial Intelligence
ISSN1989-1660
IssueSpecial Issue on Artificial Intelligence Underpinning
Volume4
Number1
Date Published09/2016
Pagination31-36
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.

KeywordsArabic Documents, Components, Hidden Markov Models, Text Classification
DOI10.9781/ijimai.2016.416
URLhttp://www.ijimai.org/JOURNAL/sites/default/files/files/2016/02/ijimai20164_1_6_pdf_34205.pdf
AttachmentSize
ijimai20164_1_6.pdf1.12 MB