Latest News:Index Copernicus Value (ICV) for 2013 was 3.59; 2014 was 58.17; 2015 was 64.83 and in 2016 is 79.75
Face recognition has many challenges due to illumination variations, large dimensionality, uncontrolled environments, aging and pose variations. In the recent years, Face recognition get remarkable improvement and accuracy to overcome these challenges, but matching in the heterogamous environment such as near infrared and visible spectrum is very challenging task. Matching of face images capture in near infrared spectrum (NIR) to face images of the visible spectrum (VIS) is a very challenging task. Recent research is categorized in three aspects such as face synthesis analysis, sub space methods, and local feature-based approaches. Face recognition has many challenges due to illumination variations, large dimensionality, uncontrolled environments, pose variations and aging. In the recent years, Face recognition get remarkable improvement and accuracy to overcome these challenges, but illumination change is still challenging. In this paper we study earlier research work to find challenges in the cross spectral face recognition model.