A non-parametric scale-based corner detector

A non-parametric scale-based corner detector

This paper introduces a new Harris-affine corner detector algorithm, that does not need parameters to locate corners in images, given an observation scale. Standard detectors require to fine tune the values of parameters which strictly depend on the particular input image. A quantitative comparison...

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Bibliographic Details
Published in:2008 19th International Conference on Pattern Recognition pp. 1 - 4
Main Authors: Bellavia, F., Tegolo, D., Valenti, C.
Format: Conference Proceeding
Language:English
Published: IEEE 01-12-2008
Subjects:
Application software
Autocorrelation
Computer vision
Covariance matrix
Detectors
Eigenvalues and eigenfunctions
Entropy
Image edge detection
Image segmentation
Robustness
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Description
Summary:This paper introduces a new Harris-affine corner detector algorithm, that does not need parameters to locate corners in images, given an observation scale. Standard detectors require to fine tune the values of parameters which strictly depend on the particular input image. A quantitative comparison between our implementation and a standard Harris-affine implementation provides good results, showing that the proposed methodology is robust and accurate. The benchmark consists of public images used in literature for feature detection.
ISBN:9781424421749
1424421748
ISSN:1051-4651
2831-7475
DOI:10.1109/ICPR.2008.4760976