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논문검색

High-precision Immune Computation for Secure Face Recognition

원문정보

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

저자정보

  • 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

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