0461834 20240103212513.420160823235959.9 84991279725 000383376800001 10.1016/j.cosrev.2016.05.003 17 s. P cav_un_epca*00894021574-0137211 (2016)1-17Elsevier Literature survey Biometrics Face recognition Near infrared Illumination invariant cav_un_auth*0317051 Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Farokhi Sajad UTIA-B MY Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101087 Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Flusser Jan UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0280201 Sheikh U. U. MY http://library.utia.cas.cz/separaty/2016/ZOI/flusser-0461834.pdf cav_un_auth*0314467 GA15-16928S GA ČR As a primary modality in biometrics, human face recognition has been employed widely in the computer vision domain because of its performance in a wide range of applications such as surveillance systems and forensics. Recently, near infrared (NIR) imagery has been used in many face recognition systems because of the high robustness to illumination changes in the acquired images. Even though some surveys have been conducted in this infrared domain, they have focused on thermal infrared methods rather than NIR methods. Furthermore, none of the previous infrared surveys provided comprehensive and critical analyses of NIR methods. Therefore, this paper presents an up-to-date survey of the wellknown NIR methods that are used to solve the problem of illumination. The paper includes a discussion of the benefits and drawbacks of various NIR methods. Finally, the most promising avenues for future research are highlighted. JD 2017 3 RVO:67985556 http://hdl.handle.net/11104/0261407 S 1 Article Computer Science Information Systems|Computer Science Software Engineering|Computer Science Theory Methods 0.700 Q1 Q2 2016 84991279725 SCOPUS 000383376800001 WOS cav_un_epca*0089402 Computer Science Review 1574-0137 1876-7745 Roč. 21 č. 1 2016 1 17 Elsevier