Multi-view face detection and recognition under varying illumination conditions by designing an illumination effect cancelling filter
Reza Shoja Ghiass, Emad Fatemizadeh · Signal Processing: Algorithms, Architectures, Arrangements, and Applications · 2008
This paper presents a novel approach for detection and recognition of multi-view faces whose location is unknown and the illumination conditions are varying. The detection of faces is accomplished after canceling the effect of the various illumination conditions by using a proposed filter. Because of the independency of the approach to skin color of face, the persons with every kind of skin colors are detected even in completely dark environments. Next, the detected faces are recognized. It is a well known technique to combine the feature based methods with the template based methods in face recognition. Our experiments show that we can combine some proposed aspects of the feature based methods with eigenface method which is a statistical method, and get very successful results. The illumination dependency and scaling problems of eigenface method has also been solved by a new methodology.