FACE RECOGNITION BASED ON WAVELET TRANSFORM AND GROUP DECISION MAKING APPROACH

Daubechies orthogonal wavelet transform is used to preprocess the face image,resulting in its four subimages belonging to different frequency bands.The singular value feature vectors are then extracted from the four subimages respectively,and the nearest neighbour classifier is used to recognize them.This makes correlation reduce and makes difference raise between the four groups of sort results.A group decision making algorithm is designed to combine the multiple sort results.Moreover,all of or part of them can be combined according to group consensus index.Experiments show that so far as singular value feature is concerned,there is a certain complementarity between the sort results of the four subimages.The sort performance can be improved using the group decision making algorithm,which has lower computational complexity and better combination results than the commonly used mark counting approach.