0426703 20240103204051.520140519235959.9 000337307100015 10.1007/978-981-4585-42-2_15 7 s. P cav_un_epca*0426702978-981-4585-41-5129-135NěmeckoSpringer2014SakimH.MustaffaM. Face recognition Infrared imaging Moments cav_un_auth*0280199 Farokhi S. MY cav_un_auth*0302104 Shamsuddin S.M. MY cav_un_auth*0302105 Sheikh U.U. MY cav_un_auth*0101087 Flusser Jan Zpracování obrazové informace Department of Image Processing ZOI ZOI UTIA-B Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. GAP103/11/1552 GA ČR cav_un_auth*0273618 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. cav_un_auth*0302106 The 8th International Conference on Robotic, Vision, Signal Processing & Power Applications Penang 08.12.2013-10.12.2013 MY 2015 JD 4 PR RVO:67985556 http://hdl.handle.net/11104/0233599 S 2014 000337307100015 WOS cav_un_epca*0426702 The 8th International Conference on Robotic, Vision, Signal Processing & Power Applications 978-981-4585-41-5 129 135 The 8th International Conference on Robotic, Vision, Signal Processing & Power Applications Německo Springer 2014 Lecture Notes on Electrical Engineering LNEE 291 Sakim H. 340 Mustaffa M. 340