Face Recognition System

Abstract— Recognition of face expressions of human beings by a computer is an interesting and challenging problem. Face is the most important feature of a human being. Everyone have a different face features and usually used as an identification. Recognizing different faces for humans is not a difficult task but it is difficult to identify different faces and their expressions by a system. Face expressions recognition can be used in a number of applications like authentication, security issues, and surveillance. Recently, Different Local Binary Pattern (LBP) operators have been applied into face recognition successfully. Center-symmetric Local Binary Pattern is a variation operator of LBP, which can reduce the dimensionality of LBP features,

I. INTRODUCTION
Face recognition is an active research area, and they can be used in wide range applications such as surveillance, authentication and security. Face recognition system can be used in two modes: Verification and Identification.
In the identification process, the preprocessed image of a person is compared with face images of known individuals from a large database then returns the recognized identity.
In the verification process, the preprocessed image of a person is compared with one face image from a database with the claimed identity. The system then returns the verification status by measuring the similarities between the two images. An efficient face recognition system could replace current identification methods like Personal Identification Number (PIN)-codes, passwords and Identification-cards, which according to could be exposed to security attacks, but also extremely reliable methods of biometric person identification, like fingerprint analysis and retinal or iris scans .In contrast, face recognition system is more accurate and reliable than all the proposed

Face is the most important feature of a human being. Everyone have a different face features and usually used as an identification. Recognizing different faces for humans is not a difficult task for human beings but it is difficult to identify different faces and their expressions by a system. Face expression recognition can be used in a number of applications like authentication, security issues, and surveillance. Face is a complex multidimensional structure and needs a good computing technique for recognition. Various face expression recognition techniques include Local Binary Pattern(LBP), Principal Component Analysis(PCA), Local Discriminate Analysis(LDA), Linear programming. Basic technique used for face expression recognition is local binary pattern. Local binary pattern uses the concept of threshold with the neighbouring pixels. A number of variants of LBP exist like Rotation in-variant LBP, improved LBP, Advanced LBP, and Modified LBP. In this thesis we will implement CS-LBP for face recognition by three level face