Title :
Techniques for language identification for hybrid Arabic-English document images
Author :
Elgammal, Ahmed M. ; Ismail, Mohamed A.
Author_Institution :
Dept. of Comput. Sci., Maryland Univ., College Park, MD, USA
fDate :
6/23/1905 12:00:00 AM
Abstract :
Because of the different characteristics of Arabic language and Romance and Anglo Saxon languages, recognition of documents written in hybrids of these languages requires that the language of the text is to be identified prior to the recognition phase. In this paper, three efficient techniques that can be used to discriminate between text written in Arabic script and text written in English script are presented and evaluated. These techniques address the language identification problem on the word level and on text level. The characteristics of horizontal projection profiles as well as runlength histograms for text written in both languages are the basic features underlying these techniques. Solving this problem is very important in building bilingual document image analysis systems which are capable of processing documents containing hybrid Arabic/Romance and Anglo Saxon languages
Keywords :
character recognition; document image processing; natural languages; neural nets; text analysis; Anglo Saxon; Arabic; Romance; bilingual document image analysis; document image analysis; language identification; multi-lingual document image analysis; multi-lingual environment; Character recognition; Computer science; Educational institutions; Image analysis; Image recognition; Natural languages; Optical character recognition software; TV; Text analysis; Text recognition;
Conference_Titel :
Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7695-1263-1
DOI :
10.1109/ICDAR.2001.953956