0390234 20240103202316.320130312235959.9 000322079000003 10.1117/1.JEI.22.1.013030 12 s. P cav_un_epca*02537101017-9909221 (2013)1-11 face recognition infrared imaging image moments cav_un_auth*0280199 Farokhi S. MY cav_un_auth*0280200 Shamsuddin S. M. 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. cav_un_auth*0280201 Sheikh U. U. MY cav_un_auth*0290073 Khansari M. IR cav_un_auth*0290074 Jafari-Khouzani K. US http://library.utia.cas.cz/separaty/2013/ZOI/flusser-rotation and noise invariant near-infrared face recognition by means of zernike moments and spectral regression discriminant analysis.pdf GAP103/11/1552 GA ČR cav_un_auth*0273618 Face recognition is a rapidly growing research area, which is based heavily on the methods of machine learning, computer vision, and image processing.We propose a rotation and noise invariant near-infrared face-recognition system using an orthogonal invariant moment, namely, Zernike moments (ZMs) as a feature extractor in the near-infrared domain and spectral regression discriminant analysis (SRDA) as an efficient algorithm to decrease the computational complexity of the system, enhance the discrimination power of features, and solve the “small sample size” problem simultaneously. Experimental results based on the CASIA NIR database show the noise robustness and rotation invariance of the proposed approach. Further analysis shows that SRDA as a sophisticated technique, improves the accuracy and time complexity of the system compared with other data reduction methods such as linear discriminant analysis. 2014 JD http://hdl.handle.net/11104/0219539 ENGINEERINGELECTRICALELECTRONIC|IMAGINGSCIENCEPHOTOGRAPHICTECHNOLOGY|OPTICS 1.024 0.115 7.I 0.00256 0.31 1255 191 0.311 ScienceCitationIndexExpanded Q2 26.076 32.337 Q4 Q3 2013 000322079000003 WOS cav_un_epca*0253710 Journal of Electronic Imaging 1017-9909 1560-229X Roč. 22 č. 1 2013 1 11