Language identification in historical Afghan manuscripts

Author

Farooq, Faisal ; Govindaraju, Venu

Author_Institution

CEDAR, State Univ. of New York, Amherst, NY

fYear

2007

fDate

12-15 Feb. 2007

Firstpage

1

Lastpage

4

Abstract

Automatic language identification is an important step prior to optical character recognition (OCR). In this paper we present a system to discriminate between Arabic and Persian in historical Afghan manuscripts. The classification is performed at a sub-sentence level. We propose a feature extraction algorithm for a sub-sentence based on Gabor filters followed by classification using a support vector machine (SVM). An overall precision of 96.72% and 94.90% is obtained for Persian and Arabic respectively.

Keywords

Gabor filters; feature extraction; history; image classification; natural language processing; optical character recognition; support vector machines; Gabor filters; Persian; automatic language identification; feature extraction algorithm; historical Afghan manuscripts; optical character recognition; sub-sentence classification; support vector machine; Character recognition; Feature extraction; Gabor filters; Optical character recognition software; Optical filters; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on

Conference_Location

Sharjah

Print_ISBN

978-1-4244-0778-1

Electronic_ISBN

978-1-4244-1779-8

Type

conf

DOI

10.1109/ISSPA.2007.4555588

Filename

4555588