"Face Recognition: Using Principle Component Analysis and Independent Component Analysis"
Kaizad Gotla 2002
Abstract
Recently there has been a great deal of interest in biometric means of identifying people. Due to the increasing unreliability of photo IDs, face recognition has emerged as a fairly inexpensive, reliable and fast tool in human identification. Principle Component Analysis and Independent Component Analysis are two of the most common tools used in face algorithms. This thesis attempts to describe the theories associated with these two techniques. Moreover their performances are evaluated by testing face data in MatLab.