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Proceedings Paper

A rotation invariant local Zernike moment based interest point detector
Author(s): Gökhan Özbulak; Muhittin Gökmen
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Paper Abstract

Detection of interesting points in the image is an important phase when considering object detection problem in computer vision. Corners are good candidates as such interest points. In this study, by optimizing corner model of Ghosal based on local Zernike moments (LZM) and using LZM representation Sariyanidi presented, a rotation-invariant interest point detector is proposed. The performance of proposed detector is evaluated by using Mikolajczyk's dataset prepared for rotation-invariance and our method outperforms well-known methods such as SIFT and SURF in terms of repeatability criterion.

Paper Details

Date Published: 14 February 2015
PDF: 8 pages
Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 94450E (14 February 2015); doi: 10.1117/12.2181058
Show Author Affiliations
Gökhan Özbulak, Istanbul Technical Univ. (Turkey)
Muhittin Gökmen, Istanbul Technical Univ. (Turkey)

Published in SPIE Proceedings Vol. 9445:
Seventh International Conference on Machine Vision (ICMV 2014)
Antanas Verikas; Branislav Vuksanovic; Petia Radeva; Jianhong Zhou, Editor(s)

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