A central problem in object recognition is to determine the transformation that relates the model to the image, given some partial correspondence between the two. This is useful in determining whether an object is present in an image, and if so, in determining where the object is. We present a novel method of solving this problem that uses region information. In our approach, the model is divided into volumes and the image is divided into regions. Given a match between subsets of volumes and regions (without any explicit correspondence between different pieces of the regions), the alignment transformation is computed. The method applies to planar objects under similarity, affine and projective transformations and to projections of 3D objects undergoing affine and projective transformations.