Image identification plays an important role in various domains such as in bio-metrics for identification of a person, medical image processing, law enforcement and commercial application. In the field of bio-metrics, there are many reliable identification methods such as fingerprint, retina, iris scan and Face Recognition. These methods requires user cooperation whereas Face Recognition can work without user cooperation by taking image from camera. Face Recognition is a two step process, involving face detection and then recognition. In Face Detection process, face is located in a digital image or in a frame of video and in the Recognition process system identifies the face’s identity on the basis of stored images. For the Face Recognition various techniques are available such as Principal Component Analysis, Local Binary Pattern, Independent Component Analysis and many deep learning based techniques FaceNet, FaceID, DeepFace etc. These techniques have their own advantages and disadvantages for example many techniques suffer from head rotation, pose, makeup, hair style and image quality. In this paper, we present a review of the previous work done in this field. Also discussion about the process of recognition, preprocessing for Face Recognition techniques, classification of face detection and recognition techniques and an analysis of existing work has been presented.

Face Recognition, Face Detection, Deep learning, Image pre-processing, Bio-metrics, Principal Component Analysis

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