Face Recognition Using Principal Component Analysis with Median for Normalization on a Heterogeneous Data Set

Abstract

Recognizing Faces helps to name the various subjects present in the image. This work focuses on labeling faces on an image which includes faces of humans being of various age group (heterogeneous set ). Principal component analysis concentrates on finds the mean of the data set and subtracts the mean value from the data set with an intention to normalize that data. Normalization with respect to image is the removal of common features from the data set. This work brings in the novel idea of deploying the median another measure of central tendency fornormalization rather than mean. The above work was implemented using matlab. Results show that Median is the best measure for normalization for a heterogeneous data set which gives raise to outliers.