This paper proposes a new single sample face recognition algorithm based on matrix QR decomposition and 2DLDA. The algorithm uses QR decomposition of a matrix on the single sample

extracts the effective information to constitute a virtual image

combines the original training images and generates a new training sample set

then the application of 2DLDA algorithm for feature extraction and recognition. The algorithm is tested on ORL face database

experimental results show that this algorithm is not only superior to the traditional algorithms on recognition rate

such as PCA

SPCA

(PC) A

E(PC)A algorithms

but also has good robustness for factors such as illumination

expression etc.