Face recognition has been always a hot spot in image processing and pattern recognition. However

problems

such as small samples

rotation

and scale changes

always restrict its development. In this paper

a scale invariant feature and template based method is proposed to achieve recognition upon a single face sample. First

scale invariant features are extracted and matched to obtain feature-level correspondence between faces

upon which rotation and scale variances between faces can be estimated and rectified for invariant templates. Then a sub-region based zero mean Nermaczed Cross-Correlation (ZNCC) method will be adopted to acquire region-level correspondences between the templates and rectified faces. Finally

a joint judgment will be made according to both feature-level and region-level correspondences between faces. This method is feasible and robust not only to rotation

scale and illumination variance

but also to low texture.