Using Eigenface Features to Drive Support Vector Machines in Face Recognition Systems
Face recognition is one of the growing fields of research which has deep rooted applications in authentication
domains. Its success can be attributed to the various algorithms which have strived to make it work in the real time. The
major factor underlying such systems is the proper feature extraction and effective classification. The paper aims at using the
two most well-known techniques to accomplish the above mentioned factors. They are Eigenface method -to extract features
and Support vector Machines (SVM) –to classify the data. It was found that the proposed methodology was effective in
terms of classification and due to the ease of implementation; it can be adopted in real-world applications.