A non-parametric scale-based corner detector

Author

Bellavia, F. ; Tegolo, D. ; Valenti, C.

Author_Institution

Dipt. di Mat. e Applicazioni, Univ. degli Studi di Palermo, Palermo, Italy

fYear

2008

fDate

8-11 Dec. 2008

Firstpage

1

Lastpage

4

Abstract

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.

Keywords

affine transforms; edge detection; feature extraction; image classification; image enhancement; image reconstruction; image segmentation; Harris-affine corner detector algorithm; Hessian-affine detector; feature extraction; image classification; image contrast enhancement; image mosaicing; multiple-views reconstruction; nonparametric scale-based image corner detector; Application software; Autocorrelation; Computer vision; Covariance matrix; Detectors; Eigenvalues and eigenfunctions; Entropy; Image edge detection; Image segmentation; Robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2008. ICPR 2008. 19th International Conference on

Conference_Location

Tampa, FL

ISSN

1051-4651

Print_ISBN

978-1-4244-2174-9

Electronic_ISBN

1051-4651

Type

conf

DOI

10.1109/ICPR.2008.4760976

Filename

4760976