14 February 2015 A rotation invariant local Zernike moment based interest point detector
Author Affiliations +
Proceedings Volume 9445, Seventh International Conference on Machine Vision (ICMV 2014); 94450E (2015) https://doi.org/10.1117/12.2181058
Event: Seventh International Conference on Machine Vision (ICMV 2014), 2014, Milan, Italy
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 et.al 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.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gökhan Özbulak, Gökhan Özbulak, Muhittin Gökmen, Muhittin Gökmen, } "A rotation invariant local Zernike moment based interest point detector", Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 94450E (14 February 2015); doi: 10.1117/12.2181058; https://doi.org/10.1117/12.2181058
PROCEEDINGS
8 PAGES


SHARE
RELATED CONTENT


Back to Top