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Corner detection by Local Zernike Moments

Access

info:eu-repo/semantics/closedAccess

Date

2015

Author

Ozbulak, Gokhan
Gökmen, Muhittin

Metadata

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Citation

Ozbulak, G., Gokmen, M., (2015) Corner detection by Local Zernike Moments. Conference: 23nd Signal Processing and Communications Applications Conference (SIU) Location: Inonu Univ, Malatya, TURKEY. p. 1354-1357.

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.

Source

Conference: 23nd Signal Processing and Communications Applications Conference (SIU) Location: Inonu Univ, Malatya, TURKEY Date: MAY 16-19, 2015

URI

https://hdl.handle.net/20.500.11779/660

Collections

  • Araştırma Çıktıları, WOS İndeksli Yayınlar Koleksiyonu [433]
  • MF, BM, Bildiri ve Sunum Koleksiyonu [29]



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