Isomap Algorithm Based on 2D Gabor Wavelets and 2DPCA

Compared with gray feature, the Gabor feature is more effective for facial image representation. But in practice, the dimension of a Gabor feature is so high that the computation is prohibitively large. In this paper, We use the two-dimensional principal component analysis???2DPCA???to reduce the dimension and then replace the original gray feature with the Gabor feature vector of reduced dimension as the front-end input of traditional Isometric Mapping(Isomap) algorithm. The validity of this method can be verified by experimental results.