Handwritten Arabic word recognition based on Ridgelet transform and support vector machines

Author

Nemmour, Hassiba ; Chibani, Youcef

Author_Institution

Signal Process. Lab., Univ. of Sci. & Technol. Houari Boumediene, Algiers, Algeria

fYear

2011

fDate

4-8 July 2011

Firstpage

357

Lastpage

361

Abstract

We propose a method for handwritten Arabic word recognition based on the combination of the Ridgelet transform and SVMs. Ridgelets are used for generating pertinent features of handwritten words while the classification stage is based on the One-Against-All multiclass implementation of SVMs. The experimental investigation is conducted on a vocabulary of twenty-four words extracted from the ITN/ENIT database. The Ridgelet performance is assessed comparatively to the results obtained for Radon and uniform grid (zoning) features. Results highlight the reliability of the Ridgelet-SVM combination for handwritten Arabic word recognition.

Keywords

handwriting recognition; handwritten character recognition; natural languages; pattern classification; support vector machines; transforms; SVM; classification stage; handwritten Arabic word recognition; one-against-all multiclass implementation; ridgelet transform; support vector machine; Character recognition; Handwriting recognition; Hidden Markov models; Support vector machines; Wavelet transforms; Handwritten arabic word; Ridgelet transform; SVMs;

fLanguage

English

Publisher

ieee

Conference_Titel

High Performance Computing and Simulation (HPCS), 2011 International Conference on

Conference_Location

Istanbul

Print_ISBN

978-1-61284-380-3

Type

conf

DOI

10.1109/HPCSim.2011.5999846

Filename

5999846