Face Recognition Based on Projection Map and Fourier Transform for One Training Image Per Person
Jiazhong He, Di Zhang · 2009
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 person is available. In this paper, we present a method of face recognition based on projection map and Fourier Transform to solve the one training sample problem. To acquire more information from the single training sample, each original training image is linearly combined with its projection map into a new training image. By using Fourier transform, the Fourier spectrum of face image is obtained that is invariant against spatial translation. The LI distance classifier is adopted in recognition. The proposed algorithm obtains acceptable experimental results on the ORL face database.