DESIGN OF FACE RECOGNITION SYSTEM USING PRINCIPAL COMPONENT ANALYSIS

Abin Abraham Oommen, C. Senthil Singh, M. Manikandan

Abstract: Face is considered to be one of the most important visual objects for identification. Recognition of human face is complex and it converts the face into a mathematical model. Face recognition is the most efficient and sophisticated method for the security systems. It is a biometric technology with a wide range of applications such as use in ATM machines, preventing voter’s fraud, criminal identification, human computer interaction, etc. This paper describes the building of a face recognition system by using Principal Component Analysis method. PCA is the method for reduce the data dimension of the image. It is based on the approach that breaks the face images into a small set of characteristic feature images. These“eigenfaces” are the principal components of the initial data set of face images. Recognition is done by comparing the input face image with the faces in the data set through distance measuring methods. Here the face recognition system is developed using Matlab and it recognizes the input face from a set of training faces

Keywords: Principal Component Analysis, eigenfaces, training faces

DOI: https://doi.org/10.15623/ijret.2014.0313002