Development and evaluation of fast branch-and-bound algorithm for feature matching based on line segments |
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Authors: | Lik-Kwan Shark [Author Vitae] Andrey A. Kurekin [Author Vitae] [Author Vitae] |
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Affiliation: | a ADSIP Research Centre, Department of Technology, University of Central Lancashire, Preston PR1 2HE, UK b Department of Computer Science, Cardiff University, Cardiff CF24 3AA, UK |
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Abstract: | By extending the previously proposed geometric branch-and-bound algorithm with bounded alignment for point pattern matching, the paper presents the development and evaluation of a new and fast algorithm for image registration based on line segments. Using synthetically generated data sets with randomly distributed line segments and hard test cases with highly symmetric line patterns, as well as real remote sensing images, the developed algorithm is shown to be computationally fast, highly robust, capable of handling severely corrupted data sets with considerable line segment position errors as well as significant fragmented and spurious line segments in the images to be matched. |
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Keywords: | Feature matching Hausdorff distance Line segment matching Branch and bound Bounded alignment |
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