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

— 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. Keywords — Text Line Segmentation, Handwritten Arabic Document, Connected Component Analysis, Markov Decision Processes.

• Type: Journal
• Year: 2016
• Where: IJIMAI
• Authors: Youssef Boulid, Abdelghani Souhar, Mohamed Youss Elkettani
• Keywords: IJIMAI 2016