Evaluation Approach of Arabic Character Recognition

Author:

Aljuaid Hanan1,Mohamad Dzulkifli1,Sarfraz Muhammad2

Affiliation:

1. University Technology Malaysia, Malaysia

2. Kuwait University, Kuwait

Abstract

This paper proposes and contributes towards designing a complete system for off-line Arabic character recognition. The proposed system is specifically meant for Arabic handwriting recognition, but it equally works for the typed character recognition. It has various phases including preprocessing and segmentation. It also includes thinning phase and finds vertical and horizontal projection profiles. The recognition phase is managed by genetic algorithm. The genetic algorithm stands on feature extraction algorithm that defines six features for each segment. The algorithm, for Arabic handwriting recognition, obtained 90.46 recognition rate. The proposed system has been compared with other systems in the literature. It has achieved the second best recognition rate.

Publisher

IGI Global

Reference24 articles.

1. Abdullah, S. A. (2007). Off-line handwritten Arabic characters segmentation using rotation invariant segment feature (RISF). International Arab Journal of Information Technology, 5(2).

2. Combining Slanted-Frame Classifiers for Improved HMM-Based Arabic Handwriting Recognition

3. Alimi, A. M. (1997). An evolutionary neuro-fuzzy approach. In Proceedings of the 4th IEEE International Conference on Document Analysis and Recognition (pp. 382-386).

4. Aljuaid, H., Mohamad, D., & Sarfraz, M. (2009). Arabic handwriting recognition using projection profile and genetic approach. In Proceedings of the 5th International Conference in Signal Image Technologies and Information Based System (pp. 118-125).

5. Classification of Arabic script using multiple sources of information: State of the art and perspectives

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