DocumentCode :
2018999
Title :
Adaptive dissection based subword segmentation of printed Arabic text
Author :
Zidouri, A. ; Sarfraz, M. ; Shahab, S.A. ; Jafri, S.M.
Author_Institution :
Dept. of Electr. Eng., King Fahd Univ. of Pet. & Minerals, Dhahran, Saudi Arabia
fYear :
2005
fDate :
6-8 July 2005
Firstpage :
239
Lastpage :
243
Abstract :
Numerous segmentation and recognition techniques have been proposed in literature for Arabic OCR system. Correct and efficient segmentation of Arabic text into characters is considered to be a fundamental problem. While OCR systems for other languages do not need segmentation for printed text for successful recognition, it is essential to design robust and powerful segmentation algorithms or employ segmentation free recognition schemes for printed Arabic text. Even more, in recognition of handwritten characters, segmentation is considered to be indispensable. Most of current segmentation technique suffers from over segmentation and under segmentation in addition to not being adaptive in nature. In this paper, we have proposed a new sub-word segmentation scheme, which is independent of font size and font type.
Keywords :
adaptive systems; handwritten character recognition; image segmentation; natural languages; optical character recognition; text analysis; Arabic OCR system; adaptive dissection based subword segmentation; printed Arabic text; Algorithm design and analysis; Character recognition; Computer science; Handwriting recognition; Minerals; Optical character recognition software; Petroleum; Prototypes; Robustness; Text recognition; Arabic Character Recognition; Word Segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Visualisation, 2005. Proceedings. Ninth International Conference on
ISSN :
1550-6037
Print_ISBN :
0-7695-2397-8
Type :
conf
DOI :
10.1109/IV.2005.17
Filename :
1509085
Link To Document :
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