At present there are many methods that could deal well with frontal view face recognition when there is sufficient number of representative training samples per person. However, few of them can work well when only single training sample per person is available. In this paper, we present a training sample enhancement method based on Wavelet Transform (WT) low-frequency band to improve the performance of face recognition with a single training sample. In order to enhance the classification information of the single training sample, each training sample is combined with its WT reconstructed image based on low-frequency band into a new training sample. By using Fourier transform, the resulting spectrum representation of face image is used as the feature of the face image for recognition. The experimental results on ORL face database indicate the effectiveness of the proposed method.
A New Image Enhancement Method for Face Recognition with Single Training Sample
2008 Congress on Image and Signal Processing ; 3 ; 216-219
2008-05-01
293692 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Component-based LDA Method for Face Recognition with One Training Sample
British Library Conference Proceedings | 2003
|British Library Online Contents | 2015
|Face image recognition method and recognition device thereof
Europäisches Patentamt | 2020
|