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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 transformation between images and tackles very challenging situations that usually lead to pairing ambiguities, such as repetitive patterns in the images. The registration itself is performed through an efficient level-line cumulative matching based on a multistage primitive election procedure. Each stage provides a coarse estimate of the transformation that the next stage gets to refine. Although we deal with similarity transforms (rotation, scale and translation), our approach can be easily adapted to more general transformations.