A new algorithm for detecting corners in digital images

Authors:
Eduard Sojka
Affiliations:
Technical University of Ostrava
Venue:
SCCG '02 Proceedings of the 18th spring conference on Computer graphics
Year:
2002

Citing 3
Cited 1

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A comprehensive review of current local features for computer vision

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Abstract

Corners and vertices are important features in images, which are frequently used for scene analysis, stereo matching and object tracking. Many algorithms for detecting the corners have been reported up to now. In this paper, a new algorithm is presented. The algorithm is based on measuring the variance of the directions of the gradient of brightness. The probability of the event that a point belongs to the approximation of a straight segment of the isoline of brightness passing through the point being tested is computed using the technique of Bayesian estimations and used as a weight. The algorithm is presented both from the theoretical and from the practical point of view. The results of tests show that the algorithm is better than other known algorithms that are usually used for solving the problem.