Face recognition using Principal Component Analysis

Abstract

Facial recognition as a basic biometric technology has become increasingly important in the field of research because of its non-intrusive and non-contact nature. The work in this memoir focuses on the automatic identification of faces and should allow facial recognition, using a reference database that contains photos of known people and presenting to the algorithm the face of a person to identify . Principal Components Analysis (PCA) aims to reduce the size of the workspace to simplify the data and their interpretation. The goal is to take into account important information that will recognize a face among others with a good success rate. Recognition is therefore limited to the use of two-dimensional images and the method used is global, since it analyzes the entire face. To validate this work, we test this technique on a Cambridge ORL and JAFFE face database.