Near Infrared Face Recognition: A Comparison of Moment-Based Approaches

0426703 - ÚTIA 2015 RIV DE eng C - Konferenční příspěvek (zahraniční konf.)
Farokhi, S. - Shamsuddin, S.M. - Sheikh, U.U. - Flusser, Jan
Near Infrared Face Recognition: A Comparison of Moment-Based Approaches.
The 8th International Conference on Robotic, Vision, Signal Processing & Power Applications. Německo: Springer, 2014 - (Sakim, H.; Mustaffa, M.), s. 129-135. Lecture Notes on Electrical Engineering, LNEE 291. ISBN 978-981-4585-41-5.
[The 8th International Conference on Robotic, Vision, Signal Processing & Power Applications. Penang (MY), 08.12.2013-10.12.2013]
Grant CEP: GA ČR GAP103/11/1552
Institucionální podpora: RVO:67985556
Klíčová slova: Face recognition * Infrared imaging * Moments
Kód oboru RIV: JD - Využití počítačů, robotika a její aplikace

Moment based methods have evolved into a powerful tool for face recognition applications. In this paper, a comparative study on moments based feature extraction methods in terms of their capability to recognize facial images with different challenges is done to evaluate the performance of different type of moments. The moments include Geometric moments (GM’s), Zernike moments (ZM’s), Pseudo-Zernike moments (PZM’s) and Wavelet moments (WM’s). Experiments conducted on CASIA NIR database showed that Zernike moments outperformed other moment-based methods for facial images with different challenges such as facial expressions, head pose and noise.
Trvalý link: http://hdl.handle.net/11104/0233599