This paper mainly presents face recognition system based on principal component analysis. The goal is to implement the system which is able to distinguish a single face from the larger database. In this research work we are compressing the image using the mathematical tool principal component analysis and then recognize the image from the same data set by the model. First we will describe the basic concepts prevailing with principal component analysis. Then we will see that how principal component can be extracted from a given data set. Then we will go for sampling distribution of Eigen values and Eigen vectors. Then followed by model adequacy test, then we perform our task of image detection. The problem arises when we use high dimensionality space. Because in face or in 3d image, we have different eigen values or vectors and it can’t be fixed due to high dimensions as compared to 2d image. Hence, we use Principal Component Analysis (PCA).

PCA, Eigen values, Eigen vectors, image compression. Dimension reduction

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