Face Recognition Using the Concept of Principal Component Analysis

Face Recognition has been an active area of research in image processing and computer vision due to its extensive range of applications relating to biometrics, smart cards, identity authentication, and security systems etc. This paper provides a real time application of Face Recognition system based on holistic matching method. Here, we use a concept of principal component analysis (PCA) by decomposing face images into a small set of feature images called eigenfaces. Later we compute the distance between test face image in face space with those of known face classes and recognize the face as a known with one that as minimum distance. Finally we plot confusion matrix, which allows visualization of the performance of an algorithm.