Image registration is a fundamental object recognition method in computer vision. It aims to find a best match of an object image in an image to be processed. In this paper

we concentrate on image registration from image feature point-sets. A new method is proposed which is based on the conventional correlation measure of two point-sets which was introduced by Umeyama. The traditional Procrustes analysis method is used to normalize the point-sets. The novelty of the proposed method is by introducing a weight matrix into Umeyama' s correlation measure the limitation of the traditional method

which requires the dimensions of both point-sets to be the same

is released. The proposed method can register two point-sets with geometrical distortion and different dimensions. Point-sets registration results are given in the paper. When the dimensions of both point-sets are the same

both of the proposed method and the traditional method work well. But when the dimensions are different

only the proposed method can register point-sets precisely.