Discrimination between Arabic and Latin from bilingual documents

Author

Haboubi, Sofiene ; Maddouri, Samia Snoussi ; Amiri, Hamid

Author_Institution

Syst. & Signal Process. Lab., Nat. Eng. Sch. of Tunis, Tunis, Tunisia

fYear

2011

fDate

3-5 March 2011

Firstpage

1

Lastpage

6

Abstract

An important task in machine learning is the electronic reading of documents. In this process, discrimination between languages is one of the first steps in the problem of automatic document text recognition. We are interested in the processing of mixed Arabic/Latin printed documents. Our method is based essentially on the extraction of words. We first extract structural features of words and then recognize the writing language. We finally present the results of our classification approach and discuss possible improvements.

Keywords

learning (artificial intelligence); natural language processing; text analysis; Arabic/Latin printed document; automatic document text recognition; bilingual document; electronic document reading; machine learning; structural features extraction; Character recognition; Feature extraction; Gabor filters; IEEE Computer Society; Optical character recognition software; Text analysis; USA Councils; Language identification; structural features; word extraction;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications, Computing and Control Applications (CCCA), 2011 International Conference on

Conference_Location

Hammamet

Print_ISBN

978-1-4244-9795-9

Type

conf

DOI

10.1109/CCCA.2011.6031496

Filename

6031496