In the present world, biometric systems are used to analyze and verify a person's distinctive bodily or behavioral features for authentication or recognition. Till now, there are numerous authentication systems that use iris, fingerprint, and face feature for identification and verification where the face recognition based systems are most widely preferred as they do not require user help every time in it and are more automated and easy to function. This review paper provides a comparative study between various face recognition techniques and their hybrid combination. The most commonly used datasets in this domain are also analyzed and reviewed. We have also highlighted the future scope and challenges in this domain, as well as various Deep Learning (DL) based algorithms for facial recognition.
Key words: Face Recognition, Local binary pattern, Convolutional neural networks, Principal component analysis, and Histogram of oriented gradient.