Combining online and offline systems for Arabic handwriting recognition

Author

Azeem, S.A. ; Ahmed, Hameeza

Author_Institution

Electron. Eng. Dept., American Univ. in Cairo (AUC), Cairo, Egypt

fYear

2012

fDate

11-15 Nov. 2012

Firstpage

3725

Lastpage

3728

Abstract

The purpose of this research is to improve the recognition rate of online Arabic handwriting recognition using HMM (Hidden Markov Model). Delayed strokes are removed from the online Arabic word to avoid the difficulty and the confusion caused by the delayed strokes in the recognition process. A new technique for extracting offline features by dividing the image into non-uniform horizontal segments is presented. The integration between online and offline approaches has proven to give a better performance. With the combination we could increase the system performance over the best individual recognizer by 2.38%.

Keywords

feature extraction; handwriting recognition; hidden Markov models; image segmentation; natural language processing; text analysis; HMM; delayed stroke removal; hidden Markov model; image segmentation; nonuniform horizontal segments; offline feature extraction; offline system; online Arabic handwriting recognition; online Arabic word; online system; recognition rate improvement; Databases; Dictionaries; Feature extraction; Handwriting recognition; Hidden Markov models; Image segmentation; Speech recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition (ICPR), 2012 21st International Conference on

Conference_Location

Tsukuba

ISSN

1051-4651

Print_ISBN

978-1-4673-2216-4

Type

conf

Filename

6460974