Face Recognition using Principal Component Analysis and ANN

Abstract: Human Face detection is the process of identifying the features of faces to detect the faces on the basis of the discriminant features. Features of faces are eyes, ears, eyebrows, nose, lips, hairs, chicks, forehead etc. Face detection can be carried out using these features of faces. Face is important part to identify the person. It can be used as the computer visual application. Face is the important part of our body by which it is easy to identify and recognize the person. Face detection is one of the challenging tasks as there are many issues such as changes in the appearances of faces, variations in poses, noise, distortion and illumination condition. In this paper, the framework for efficient face detection using fusion of PCA and Artificial neural network is presented. The image features are represented as reduced features space by using PCA which is a dimensionality reduction technique. Further these features are given as input to the ANN for training. Multilayer perceptron network is used here for accomplishing this task.

Keywords: PCA, Eigen faces, Eigen space, Face Detection, Face recognition, ANN.