• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.19-26
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• 2009

This paper studies on the recognition rate change with respect to illumination variance and the confidence level of PCA(Principal Component Analysis) based face recognition by measuring the cumulative match score of CMC(Cumulative Match Characteristic). We studied on the confidence level of the algorithm under illumination changes and selection of training images not only by testing multiple training images per person with illumination variance and single training image and but also by changing the illumination conditions of testing images. The experiment shows that the recognition rate drops for multiple training image case compared to single training image case. We, however, confirmed the confidence level of the algorithm under illumination variance by the fact that the training image which corresponds to the identity of testing image belongs to upper similarity lists regardless of illumination changes and the number of training images.