Spectroface is a face representation method using wavelet transform and Fourier transform and have been prove to be invariant to translation and tolerant to expression variety. In this paper

the two important issues on Spectroface system is studied. One is how to preprocess system

another is the selection of similarity measurement. The moment is employed to preprocess system that it is good method to normalizing the scale and rotation of human face. The similarity measurement has been selected by comparing four typical kinds of similarity measurement

i.e.

nearest neighbor method

averaging method

Hausdorff distance method and modified Hausdorff distance method(MH). Nearest neighbor method

averaging method and modified Hausdorff distance method are good for Spectroface. Nearest neighbor method is the most effective method in the recognition of frontal faces with translation

scale

rotation

different facial expressions

small pose

small occlusion and different illumination condition. It gives high accuracy as 97% and 99% in Yale and Olivetti face image databases respectively.