Face Recognition Based on Image Enhancement and Fourier Spectrum for One Training Image per Person
Minghui Du · Science Technology and Engineering · 2006
At present there are many methods that could deal well with frontal view face recognition when there is sufficient number of representative training samples. However, few of them can work well when only one training sample per class is available. In order to enhance the classification information of the single training sample, each training sample is combined with its reconstructed image gotten by perturbing the image's singular values into a new training sample. The Fourier spectrum is used as feature for recognition. Experimental results on ORL show the effectiveness of the method.