DocumentCode :
1582570
Title :
A graph-based segmentation and feature extraction framework for Arabic text recognition
Author :
Elgammal, Ahmed M. ; Ismail, Mohamed A.
Author_Institution :
Dept. of Comput. Sci., Maryland Univ., College Park, MD, USA
fYear :
2001
fDate :
6/23/1905 12:00:00 AM
Firstpage :
622
Lastpage :
626
Abstract :
This paper presents a graph-based framework for the segmentation of Arabic text. The same framework is used to extract font independent structural features from the text that are used in the recognition. The major contribution of this paper is a new graph-based structural segmentation approach based on the topological relation between the baseline and the line adjacency graph representation of the text. The text is segmented to sub-character units that we call "scripts". A structure analysis approach is used for recognition of these units. A different classifier is used to recognize dots and diacritic signs. The final character recognition is achieved by using a regular grammar that describes how characters are composed from scripts
Keywords :
character recognition; edge detection; feature extraction; graph theory; image segmentation; Arabic text recognition; baseline detection; character recognition; feature extraction; line adjacency graph; regular grammar; script segmentation; Character recognition; Computer science; Educational institutions; Error analysis; Feature extraction; Optical character recognition software; Structural shapes; Text recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7695-1263-1
Type :
conf
DOI :
10.1109/ICDAR.2001.953864
Filename :
953864
Link To Document :
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