Face Recognition

Identifying a human individual from his or her face is one of the most nonin-trusive modalities in biometrics. However, it is also one of the most challenging ones. This chapter discusses why it is challenging and the factors that a practitioner can take advantage of in developing a practical face recognition system. Some major existing approaches are discussed along with some algorithmic considerations. A face recognition algorithm is presented as an example along with some experimental data. Some possible future research directions are outlined at the end of the chapter. 1.1 INTRODUCTION Face recognition from images is a sub-area of the general object recognition problem. It is of particular interest in a wide variety of applications. Applications in law enforcement for mugshot identiication, veriication for personal identiication such as driver's licenses and credit cards, gateways to limited access areas, surveillance of crowd behavior are all potential applications of a successful face recognition system. The environment surrounding a face recognition application can cover a wide spectrum | from a well controlled environment to an uncontrolled one. In a controlled environment, frontal and proole photographs of human faces are taken, complete with a uniform background and identical poses among the participants. These face images are commonly called mug shots. Each mug shot can be manually or automatically cropped to extract a normalized 1