A New approach for image processing using Cellular Automata

Abstract: Face recognition has been one of the most interesting and important research fields in the past two decades. The existing algorithm represents some face space with higher dimensionality and it is not effective too. Our approach treats face recognition as two dimensional recognition problems. The face is represented as the eigenfaces which is eigenvectors. The goal is to implement the system (model) for a particular face and distinguish it from a large number of stored faces with some real-time variations as well. The Eigen face approach uses Principal Component Analysis (PCA) algorithm for the recognition of the images. It gives us efficient way to find the lower dimensional space. The experimental result shows the performance of the algorithm with the plot for the variation and image recognition.

Keywords: Computer Security, Eigen Face Recognition, Eigen Vectors, Information Security, Principle Component Analysis.