Study and Analysis of Different Face Recognition Techniques Based on Graph

Human face recognition is very interesting as well as very challenging area of research. In our study of different existing face recognition schemes, we have seen that it has very important role in many applications. For this paper, we have studied and worked on the various steps of face recognition and analyzed a method to work on them. Where the face is detected from an input image and Gabor filter is applied. Then, two approaches are used (1) Delaunay triangulation and (2) Euclidean distance which are apply to the extracted feature points (which is referred as node set graph) and they are stored in the database. These store node set is used for checking the similarity with the input image. We have also compared both of the proposed approach in the system and we found that node set with Euclidean distance gives a better recognition rate.

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