Face-recognition is becoming common among the section of study in computer-vision, while it is also one of the very effective programs of comprehension and image-analysis. It may be employed for both ID and confirmation. At the moment, there are lots of means of front watch face-recognition. Nicely when just one instant picture per course can be obtained nevertheless, a handful of them can perhaps work. In this paper, we discuss the different face recognition techniques and find a better method for pose variation, non-uniform motion blur and Illumination by using a Reference face graph for face recognition. One example image' problem and two generalized eigenface algorithms are proposed. Face-recognition has been analyzed thoroughly; nevertheless, real world face-recognition stays a job that is difficult. The interest in unconstrained useful face-recognition is increasing using the surge of online media, for example, video-surveillance video, and internet sites wherever encounter evaluation is of substantial significance. Face-recognition is approached by us within data theory's framework. We identify an unfamiliar encounter utilizing an exterior Reference Face Graph (RFG). There is an RFG produced by evaluating it towards the encounters within the built RFG and acknowledgement of the given encounter is attained. Centrality steps are used to recognize encounters that were unique within the Reference Face Graph.