Face Recognition:A review of Datasets and Methods

Face is one of the popular and easiest ways of biometric to distinguish the individual identity. It has various applications in computer vision such as imposing security, entertainment, forensic, finding missing persons, etc. Face Recognition is a successful biometric identification system including fingerprints, iris, retina, hand geometry, etc that uses personal characteristics to identify the person's identity. Several challenges such as facial expressions, pose variations, occlusion, lighting conditions or illuminations, aging, etc have the great impact on the success of face recognition and reduce the performance of a system. This paper first discusses the various datasets available in the field of face recognition system with their characteristics. Later, it proposed a face recognition method using Haar cascade feature extraction and local binary pattern. Preprocessing, face selection and classification are primary steps in any face recognition system. However, the most important and crucial stage responsible for the successful face recognition system is the feature extraction.