Arabic Handwriting Texture Analysis for Writer Identification Using the DWT-Lifting Scheme

  • Authors:

  • S. Gazzah;N. Ben Amara

  • Affiliations:

  • Ecole Nationale d'Ingénieurs de Sousse, France;Ecole Nationale d'Ingénieurs de Sousse, France

  • Venue:
  • ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
  • Year:
  • 2007

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Abstract

In this paper, we present an approach for writer identification using off-line Arabic handwriting. The proposed method explores the handwriting texture analysis by 2D Discrete Wavelet Transforms using lifting scheme. A comparative evaluation between textural features extracted by 9 different wavelet transform functions was done. A modular Multilayer Perceptron classifier was used. Experiments have shown that writer identification accuracies reach best performance levels with an average rate of 95.68%. Experiments have been carried out using a database of 180 text samples. The chosen text was made to guarantee the involvement of the various internal shapes and letter locations within an Arabic subword.