A New Hybrid Approach on Face Detection and Recognition

Abstract

Face detection and recognition is an important paradigm when we consider the biometric based systems. Among various biometric elements, the face is the most reliable one and can be easily observed even from a distance as compared to iris or fingerprint which needs to be closely observed to use them for any kind of detection and recognition. Challenges faced by face detection algorithms often involve the presence of facial features such as beards, mustaches, and glasses, facial expressions, and occlusion of faces like surprised or crying. Another problem is illumination and poor lighting conditions such as in video surveillance cameras image quality and size of an image as in passport control or visa control. Complex backgrounds also make it extremely hard to detect faces. In this research work, a number of methods and research paradigms pertaining to face detection and recognition is studied at length and evaluate various face detection and recognition methods, provide a complete solution for image-based face detection and recognition with higher accuracy, a better response rate as an initial step for video surveillance.