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Robust Minimum Squared Error Classification Algorithm with Applications to Face Recognition
  • KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Robust Minimum Squared Error Classification Algorithm with Applications to Face Recognition


Abstract

Although the face almost always has an axisymmetric structure, it is generally not symmetrical image for the face image. However, the mirror image of the face image can reflect possible variation of the poses and illumination opposite to that of the original face image. A robust minimum squared error classification (RMSEC) algorithm is proposed in this paper. Concretely speaking, the original training samples and the mirror images of the original samples are taken to form a new training set, and the generated training set is used to perform the modified minimum sqreared error classification(MMSEC) algorithm. The extensive experiments show that the accuracy rate of the proposed RMSEC is greatly increased, and the the proposed RMSEC is not sensitive to the variations of the parameters.


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Cite this article

[IEEE Style]
Z. Liu, C. Yang, J. Pu, G. Liu and S. Liu, "Robust Minimum Squared Error Classification Algorithm with Applications to Face Recognition," KSII Transactions on Internet and Information Systems, vol. 10, no. 1, pp. 308-320, 2016. DOI: 10.3837/tiis.2016.01.018.

[ACM Style]
Zhonghua Liu, Chunlei Yang, Jiexin Pu, Gang Liu, and Sen Liu. 2016. Robust Minimum Squared Error Classification Algorithm with Applications to Face Recognition. KSII Transactions on Internet and Information Systems, 10, 1, (2016), 308-320. DOI: 10.3837/tiis.2016.01.018.