A face recognition system : a novel non-negative matrix factorization based approach

Abstract

Nowadays, face recognition has become an important topic in the field of biometric authentication. In this context, many researchers have worked on improving the reliability of face recognition systems and several methods were developed for this purpose. This project presents a new approach for face recognition using the Non-Negative Matrix Factorization. The overall proposed approach is implemented using Python. In addition, the results of the developed approach are compared with other approaches which are also implemented in this work. Finally, a hybrid approach was developed using the combination of multiple approaches. The comparison is performed using the Euclidean Distance and Correlation Coefficient for classification. The results show that the performance of the proposed approach and the hybrid approach are much better that the other techniques.