Image Feature Set for Correspondence Mappings

Abstract

We present a method to automatically construct features capable of putting images in correspondence with each other (i.e., registration) without requiring control points or landmarks on the images in question. Our method is based primarily on Principal Component Analysis (PCA) and a suitable image representation. The feature set is a collection of weight vectors and the correspondence mapping is done using the distances between those vectors. Only a small number of vectors is needed. While we illustrate the approach in the context of image registration, other applications of this method are possible, like distributed sensor networks, specifically when a sensor network is built up from observing devices, like camcorders, CCDs, etc. Most notably, the method could be used for image matching and retrieval, being insensitive to rotation.