Paper Info
Title
Text lines and PAWs segmentation of handwritten Arabic document by two hybrid methods
Abstract
We present in this paper two hybrid segmentation methods of handwritten Arabic script. Both methods allow the segmentation of Arabic document in text lines and the segmentation of the text line into Pieces of Arabic Words (PAWs) respectively. The particularity of these two methods is that both use a combination with Mathematical Morphology (MM). The first method uses the (MM) in the first hand and the algorithm of construction of the Outer Isothetic Cover of a digital object (OIC) named MM-OIC in the second hand. The second method combines Hough Transform (HT) and MM called HT-MM. The two proposed methods are evaluated to the three databases : IFN/ENIT-database, BSB and KSU online databases. The impact of the MM on the two proposed methods is then discussed.
Year
DOI
Venue
2014
10.1109/ATSIP.2014.6834627
ATSIP
Keywords
Field
DocType
hough transforms,document image processing,handwritten character recognition,image segmentation,information retrieval systems,mathematical morphology,text analysis,visual databases,word processing,bsb online databases,ht-mm,hough transform,ifn-enit-database,ksu online databases,mm-oic,paw segmentation,digital object outer isothetic cover,handwritten arabic document segmentation,handwritten arabic script,hybrid segmentation methods,pieces of arabic words,text line segmentation,databases,labeling
Computer vision,Scale-space segmentation,Arabic,Computer science,Mathematical morphology,Segmentation,Hough transform,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Arabic script
Conference
Citations 
PageRank 
References 
0
0.34
8
Authors
3
Name
Order
Citations
PageRank
Maddouri, S.S.100.34
Ghazouani, F.200.68
Samoud, F.B.300.34