Comparison of Different Face Recognition Algorithms
Face recognition is one of the most successful applications of image analysis and understanding and has gained much attention in recent years. Various algorithms were proposed and research groups across the world reported different and often contradictory results when comparing them. There are two approaches for the face recognition i.e. face Geometry based and face appearance based. The appearance based technique is also sub divided into two technique i.e. local feature and global feature based. The technique of local feature based are Discrete Cosine Transform (DCT).In this paper we study the two global features appearance based algorithm i.e. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) in which every face image is converted into 1D, we are using 1D for all the calculation and then compare these two algorithm with the help of FAR (False Acceptance Rate), FRR (False Rejection Rate), Time, Memory and checks which algorithm gives the better result.