Earticle

초록

영어

The study of human language comprehension machine has become a important research topic around the world. Face recognition has great potential application value in economic, security, social security, crime, military and other fields, especially in the occasions where need verification or identification of user identity. This paper presents improved Eigen face method and method for identification of multi-classifier fusion based on support vector machine. The combination of multi-classifiers method dose not only make full use of the support vector machine and high recognition rate and distance measurement, fast speed, the training and testing, but also use a distance metric results to guide the support vector machine. The experiments show that, the efficiency and the recognition accuracy of the multi-classifier combination method has higher efficiency and lower rate of error recognition.

목차

Abstract
 1. Introduction
 2. Face Recognition Method Based on Multiple Classifier Combination
  2.1 Improved Eigenface of face Recognition Method
  2.2 Face Recognition Method Based on Support Vector Machine
  2.3 Face Recognition Method Based on Multiple Classifier Combination
 3. The Experimental Results
 4. Conclusion
 References

키워드

저자

• Yang Libo [ Department of Computer Engineering, Tai Yuan University, Shanxi, 030009, China ]
• Chang Hao [ Department of Computer Engineering, Tai Yuan University, Shanxi, 030009, China ]

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