Combining multiple similarity metrics for corner matching

Hatem Khater; Farzin Deravi

doi:10.1117/12.699034

27 February 2007 Combining multiple similarity metrics for corner matching

Hatem Khater, Farzin Deravi

Proceedings Volume 6497, Image Processing: Algorithms and Systems V; 649704 (2007) https://doi.org/10.1117/12.699034
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States

Abstract

Corner matching is an important operation in digital image processing and computer vision where it is used for a range of applications including stereo vision and image registration. A number of corner similarity metrics have been developed to facilitate matching, however, any individual metric has a limited effectiveness depending on the content of images to be registered and the different types of distortions that may be present. This paper explores combining corner similarity metrics to produce more effective measures for corner matching. In particular the combination of two similarity metrics is investigated using experiments on a number of images exhibiting different types of transformations and distortions. The results suggest that a linear combination of different similarity metrics may produce more accurate and robust assessments of corner similarity.

Citation Download Citation

Hatem Khater and Farzin Deravi "Combining multiple similarity metrics for corner matching", Proc. SPIE 6497, Image Processing: Algorithms and Systems V, 649704 (27 February 2007); https://doi.org/10.1117/12.699034

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