Tractable and Reliable Registration of 2D Point Sets
Paper in proceeding, 2014

This paper introduces two new methods of registering 2D point sets over rigid transformations when the registration error is based on a robust loss function. In contrast to previous work, our methods are guaranteed to compute the optimal transformation, and at the same time, the worst-case running times are bounded by a low-degree polynomial in the number of correspondences. In practical terms, this means that there is no need to resort to ad-hoc procedures such as random sampling or local descent methods that cannot guarantee the quality of their solutions. We have tested the methods in several different settings, in particular, a thorough evaluation on two benchmarks of microscopic images used for histologic analysis of prostate cancer has been performed. Compared to the state-of-theart, our results show that the methods are both tractable and reliable despite the presence of a significant amount of outliers.


Erik Ask

Lund University

Olof Enqvist

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

Linus Svärm

Lund University

Fredrik Kahl

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

Giuseppe Lippolis

Skåne University Hospital

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 8689 PART 1 393-406
978-3-319-10589-5 (ISBN)

Subject Categories

Computer Vision and Robotics (Autonomous Systems)

Medical Image Processing





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