Friendly Arm Based Robust Kernel

Abstract

This project describes how to build a simple, yet a complete face recognition system using Principal Component Analysis, a Holistic approach. This method applies linear projection to the original image space to achieve dimensionality reduction. The system functions by projecting face images onto a feature space that spans the significant variations among known face images. The significant features known as eigen faces do not necessarily correspond to features such as ears, eyes and noses. It provides for the ability to learn and later recognize new faces in an unsupervised manner. This method is found to be fast, relatively simple, and works well in a constrained environment. Face recognition is a widely used biological recognition technology. In comparison with other identification methods, this type of recognition has direct, friendly and convenient features. The embedded face recognition system is based on arm 9 development board, using Windows operating system, detecting face by using HAAR feature, and then recognizing face by using LBP features.