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Techniques for face recognition generally fall into global and local approaches, with the principal component analysis (PCA) being the most prominent global approach. This paper uses the PCA algorithm to study the comparison and combination of infrared and typical visible-light images for face recognition. This study examines the effects of lighting change, facial expression change and passage of time between the gallery image and probe image. Experimental results indicate that when there isdoi:10.1109/amfg.2003.1240834 dblp:conf/amfg/ChenFB03 fatcat:miupr2c5bfhktfbxs3n3d3u6um