A Brief Survey on Segmentation and Classification Techniques for Face Recognition

Face detection, registration, and identification has become a fascinating subject for researchers. The huge interest in the subject originates from the need to improve accuracy of real-time applications. Numerous techniques have been recognised and presented in recent years. Acquiring data (database), pre-processing, segmentation, feature extraction, and classification are the five stages of the whole system. This survey's goal is to provide an overview of facial recognition techniques. The survey needs to take into account research papers published between 2018 and 2021 from a number of different databases. The paper provides an overview of the work performed so far to increase the efficiency of face recognition methods using hybrid methods depend on level-set based segmentation methods, support vector machine (SVM), and random forest methods.