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Image Registration Using Advanced Topology Preserving Relaxation Labeling

Authors

Chan-IL Kim, Ji-Ae Park, Su Yang, Yoon-Nyun Kim, Hee-Jun Park and Jong-Ha Lee, Keimyung University, Korea

Abstract

This paper presents a relaxation labeling technique with newly defined compatibility measures for solving a general non-rigid point matching problem. In the literature, there exists a point matching method using relaxation labeling, however, the compatibility coefficients always take a binary value zero or one depending on whether a point and a neighboring point have corresponding points. Our approach generalizes this relaxation labeling approach. The compatibility coefficients take n-discrete values which measures the correlation between edges. We use log-polar diagram to compute correlations. Through simulations, we show that this topology preserving relaxation method improves the matching performance significantly compared to other state-of-the-art algorithms such as shape context, thin plate spline-robust point matching, robust point matching by preserving local neighborhood structures and coherent point drift.

Keywords

Point pattern matching, graph matching, registration, relaxation labelling

Full Text  Volume 6, Number 8