Image Registration Using Uncertainty Transformations

Abstract

In this work we introduce a new technique for a frequently encountered problem in computer vision: image registration. The registration is computed by matching features, points and lines, in the reference image to their corresponding features in the test image among many candidate matches. Convex polygons are used to captivate the uncertainty of the transformation from the reference features to uncertainty regions in the test image in which candidate matches are to be found. We present a simple and robust method to check the consistency of the uncertainty transformation for all possible matches and construct a consistency graph. The distinction between the good matches and the rest can be computed from the information of the consistency graph. Once the good matches are determined, the registration transformation can be easily computed.