01203nas a2200229   4500000000100000000000100001008004100002260001200043653002400055653002500079653002100104653001500125100001900140700002200159700003200181245009400213856009800307300001000405490000600415520053800421022001400959       2016                            d  c09/201610aText Classification10aHidden Markov Models10aArabic Documents10aComponents1 aYoussef Boulid1 aAbdelghani Souhar1 aMohamed Elyoussfi Elkettani00aDetection of Text Lines of Handwritten Arabic Manuscripts using Markov Decision Processes  uhttp://www.ijimai.org/JOURNAL/sites/default/files/files/2016/02/ijimai20164_1_6_pdf_34205.pdf  a31-360 v43 aIn 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.  a1989-1660