Image comparison on the base of a combinatorial matching algorithm

Abstract

In this paper we compare images based on the constellation of their interest points. The fundamental technique for this comparison is our matching algorithm, that is capable to model miss- and multi-matches, while enforcing one-to-one matches. We associate an energy function for the possible matchings. In order to find the matching with the lowest energy, we reformulate this energy function as Markov Random Field and determine the matching with the lowest energy by an efficient minimization strategy. In the experiments, we compare our algorithm against the normalized cross correlation and a naive forth-and-back best neighbor match algorithm. © 2011 Springer-Verlag.