DOI
10.9781/ijimai.2016.416
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.
Source Publication
International Journal of Interactive Multimedia and Artificial Intelligence
Recommended Citation
Boulid, Youssef; Souhar, Abdelghani; and Elkettani, Mohamed Elyoussfi
(2016)
"Detection of Text Lines of Handwritten Arabic Manuscripts using Markov Decision Processes,"
International Journal of Interactive Multimedia and Artificial Intelligence: Vol. 4:
Iss.
1, Article 10.
DOI: 10.9781/ijimai.2016.416
Available at:
https://ijimai.researchcommons.org/ijimai/vol4/iss1/10
