Fast and robust planar registration by early consensus with applications to document stitching

This paper presents a fast and extremely robust feature-based method for planar registration of partly overlapping images that uses a two-stage robust fitting approach comprising a fast estimation of a transformation hypothesis (that we show is highly likely to be correct) followed by a confirmation and refinement stage. The method is particularly suited for automatic stitching of oversize documents scanned in two or more parts. We show simulations, also supported by practical experiments, that prove both the robustness and computational efficiency of the approach.