Earticle

초록

영어

In this research, we present two comparative studies; the first one is between two methods of features extraction which are the mathematical morphology, the zoning and the hybridization of these two methods. The second comparative study is between both supervised methods used in learning-classification which are the Multi-Layer Perceptron (MLP) and the Support Vector Machines (SVM) applied to cursive handwritten Tifinagh characters recognition. The obtained experimental result demonstrates that the hybrid method is most efficient and the SVM is more performing than the MLP.

목차

Abstract
 1. Introduction
 2. Recognition System
  2.1. Tifinagh Character Database
  2.2. Pre-processing
  2.3. Features Extraction
 3. Learning-classification Phase
  3.1. The Neural Networks (NNs)
  3.2. The Supports Vectors Machines
 4. Experiments and Results
  4.1. Recognition using MLP
  4.2. Recognition Using the SVM
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• B. El Kesab [ Laboratory of Information Processing and Decision Support, Faculty of Science and Technology, BP 523, Beni Mellal, Morocco ]
• C. Daoui [ Laboratory of Information Processing and Decision Support, Faculty of Science and Technology, BP 523, Beni Mellal, Morocco ]
• B. Bouikhalene [ Laboratory of Information Processing and Decision Support, Faculty of Science and Technology, BP 523, Beni Mellal, Morocco ]
• R. Salouan [ Laboratory of Information Processing and Decision Support, Faculty of Science and Technology, BP 523, Beni Mellal, Morocco ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605