Classification of Face Images Based on Gender using Dimensionality Reduction Techniques and SVM

This report presents gender classification based on facial images using dimensionality reduction techniques such as Principal Component Analysis (PCA) and Independent Component Analysis (ICA) along with Support Vector Machine (SVM). The input dataset is divided into training and testing dataset and experiments are performed by varying dataset size. The effect of performing image intensity normalization, histogram equalization, and input scaling are observed. The outcomes of the experiments are analogous to published works that apply similar techniques