A Principal Component Analysis Method for Recognition of Human Faces: Eigenfaces Approach

Facial recognition is a biometric method of identifying a person based on a picture of their face. Facial recognition system is very much important for security, surveillance and in forensics. In this paper, a face recognition system based on eigenfaces approach of Principal Component Analysis (PCA) is proposed. The eigenfaces approach based on PCA is a very accurate method of facial recognition problem as lot of features can be extracted and all of the data of the image is analyzed together without leaving any of the information. This approach is preferred in pattern recognition tasks due to its simplicity, speed and learning capability. The relevance of eigenfaces in transmission and reception of data in communication field is also experimentally analyzed.