Earticle

초록

영어

The accuracy of face recognition is very important for its security in many applications, because wrong face recognition may cause such security problems as authorization. To increase the recognition rate in such face database as ORL, a face recognition algorithm should be good at minimizing the disturbances of facial pose, illumination and expression (PIE) to this recognition. In this paper, the improved clonal selection algorithm and diverse samples are designed. The improved clonal selection algorithm searches the most similar sample for unknown face image, according to the affinity between the unknown one and the most similar sample. The affinity is newly designed to improve the adaptive matching between the object and the samples. Compared with some state-of-the-art algorithms on the ORL face database, the proposed approach outperforms the other algorithms in the recognition rate, based on the experimental results.

목차

Abstract
 1. Introduction
 2. Face Recognition Model based on High-precision Immune Computation
 3. Improved Clonal Selection Algorithm for Face Recognition
 4. Experimental Results
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Tao Gong [ College of Information S. & T., Donghua University, Engineering Research Center of Digitized Textile & Fashion Technology, Ministry of Education, Donghua University, Department of Computer Science, Purdue University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605