A new level-line registration technique is proposed for image transform estimation. This approach is robust towards contrast changes, does not require any estimate of the unknown transfomation between images and tackles very challenging situations that usually lead to pairing ambiguities: repetitive patterns in the images. The registration by itself is performed through an efficient level-line cumulative matching based on a multi-stage primitive election procedure. Each stage provides a coarse estimate of the transformation that the next stage gets to refine. Even if we deal in this paper with similarity transform (rotation, scale and translation), our approach can be easily adapted to more general transformations.