Corner detection by Local Zernike Moments

Author

Ozbulak, Gokhan ; Gokmen, Muhittin

Author_Institution

Bilgem, Kocaeli, Turkey

fYear

2015

fDate

16-19 May 2015

Firstpage

1354

Lastpage

1357

Abstract

In this paper, our corner-based interest point detector, Robust Local Zernike Moment based Features (R-LZMF), which was proved to be scale, rotation and translation-invariant, is investigated for invariance against affine transformation, lighting and blurring. Furthermore, R-LZMF´s corner detection capability with Zernike moments of order 4 is theoretically explained in detail. Experimental results on the Inria Dataset show that R-LZMF outperforms SIFT, CenSurE, ORB, BRISK and competes with SURF in terms of repeatability for images under affine transformation and photometric deformation such as lighting and blurring.

Keywords

affine transforms; edge detection; feature extraction; BRISK; CenSurE; ORB; R-LZMF corner detection capability; SIFT; affine transformation; blurring; corner-based interest point detector; image repeatability; lighting; local Zernike moments; photometric deformation; robust local Zernike moment-based features; rotation invariance; scale invariance; translation invariance; Computer vision; Conferences; Detectors; Feature extraction; Lighting; Robustness; corner detection; feature extraction; interest point detection; local Zernike moment;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Communications Applications Conference (SIU), 2015 23th

Conference_Location

Malatya

Type

conf

DOI

10.1109/SIU.2015.7130092

Filename

7130092