Earticle

초록

영어

This paper presents for isolated handwritten Arabic characters recognition a comparison between the performances in terms of precision and speediness of six hybrid methods of features extraction based on a combination between profile technique and some efficient moments. More precisely these methods are profile with Racah moment, profile with Gegenbauer moment, profile with Hahn moment, profile with Tchybechev moment and profile with orthogonal Fourier-Mellin moment, finally profile combined in the same time with all these moments. For this purpose we have used for pre-processing the character images the median filter, the thresholding, the centering and the edge detection techniques, while in order to recognize each unknown character we have employed the support vectors machine. The simulation result demonstrates that the most precise method is the profile combined with all moments but in the same time it is the less fast.

목차

Abstract
 1. Introduction
 2. The Methodology
 3. Pre-processing
 4. Features Extraction
  4.1. Profile Method
  4.2. Moments of Images
  4.3. Racah Moment
  4.4. Gegenbauer Moment
  4.5. Hahn Moment
  4.6. Tchebychev Moment
  4.7. Orthogonal Fourier-Mellin Moment
 5. Recognition
 6. Experiments and Results
 7. Conclusion
 Acknowledgements
 References

키워드

Isolated handwritten Arabic characters Median filter Thresholding Centering edge detection techniques Profile method Racah moment Gegenbauer moment Hahn moment Tchybechev moment orthogonal Fourier-Mellin moment Support Vectors Machines

저자

• R. Salouan [ Department of Mathematic and Informatic, Polydisciplinary Faculty, Sultan Moulay Slimane University, Beni Mellal, MOROCCO ]
• S. Safi [ Department of Mathematic and Informatic, Polydisciplinary Faculty, Sultan Moulay Slimane University, Beni Mellal, MOROCCO ]
• B. Bouikhalene [ Department of Mathematic and Informatic, Polydisciplinary Faculty, Sultan Moulay Slimane University, Beni Mellal, MOROCCO ]

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