Earticle

초록

영어

In this paper, we present for printed multi-oriented, multi-scaled and noisy Greek characters recognition a comparison in terms of precision, rapidity and stability between several classifiers which the first one is a probabilistic that is hidden Markov model, the second is a neuronal that is Kohonen network or self-organizing maps while the rest of other classifiers are based on a combination between these both classifiers and even more a statistical method that is K nearest neighbors in their tree different versions which are majority voting, weighted distances and fuzzy. For this purpose we have for pre-processed each character image by the median filter and the thresholding technique, then in order to extract efficiently their features, we have exploited the Krawtchouk invariant moments.

목차

Abstract
 1. Introduction
 2. The Methodology
 3. Pre-processing
 4. Features Extraction
  4.1 The Krawtchouk Moment
 5. Recognition
  5.1 Simple Classifiers
  5.2 Hybrid Classifiers
 6. Experiments and Results
 7. Conclusion
 References

키워드

저자

• 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 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605