Robust Face Recognition

The objective of this book is to propose a new algorithm for obtaining a stable face detection and recognition techniques that have the capabilities of detecting the face with different poses and under different conditions. To obtain this stability, a hybrid of Feature-Based and Template Matching approaches are used in a new manner and under different stages, robust image segmentation, filtering steps and features detection using Feature-Based approach which can work in real-time with minimal training in contrast to other approaches such as image-based approach. This work has advantages over other approaches flow out from the ability of the proposed algorithm on detecting faces with different poses (Left, Right and Frontal) in varying illumination conditions and different races. This is done by merging some already defined algorithms such as Template Matching with new proposed algorithm to strength the detection process and obtaining robust algorithm with good results. Experimental results show that the proposed method is robust under a wide range of lighting conditions, different poses and different races.The proposed method gives a correct detection rate reach 94%.