In this work we are developing a code for matching the given image with the pre given image and displaying the information about it while keeping the error limitations in mind or displaying a negation remark. This is being done by the help of matlab simple and user friendly features. Thus making it simple, efficient and providing wide applications. It is based on information theory concepts, a computational model that best describes a face, by extracting the most relevant information contained in that face. Eigenfaces approach is a principle component analysis method, in which a small set of characteristic picture are used to describe the variation between face images. Goal is to find out the eigenvectors (eigenfaces) of the covariance matrix of the distribution, spanner by a training set of face images [1]. Later, every face image is represented by a linear combination of these eigenvectors. Evaluations of these eigenvectors are quite difficult for typical image sizes but, an approximation that is suitable for practical purpose is also presented. Recognition is performed by projecting a new image into the subspace spanned by the eigenfaces and then classifying the face by comparing its position in face space with the position of known individuals. A face recognition system, based on the eigenfaces approach is proposed. Eigenfaces approach seems to be an adequate method to be used in face recognition due to its simplicity, speed and learning capability. Experimental results are given to demonstrate the viability of the proposed face recognition method.