18-08-2012, 01:08 PM
Biometric based Authentication and Identification Systems
Biometric.docx (Size: 1.42 MB / Downloads: 36)
INTRODUCTION.
Recently biometric based authentication and identification systems have received a great impetus. They have found numerous applications in surveillance, secure site access, transaction security and remote access to resources. But unlike non biometric systems they have several inherent advantages. Unlike a pin or a password it cannot be used by an unauthorized user, it does not need to be carried, and provides for positive identification. However biometric based fingerprint, iris or DNA recognition are intrusive and require the cooperation of the user. This is one the major factors why face recognition has become highly popular and an active area of research. It has the advantage of being non invasive and can be performed even at a distance, some times even without the knowledge of the user as is necessary in many security and surveillance applications.
PROBLEMS OCCURING DURING FACE RECOGNITION
Due to the dynamic nature of face images, a face recognition system encounters various problems during the recognition process. It is possible to classify a face recognition system as either “robust” or “weak” based on its recognition performances under these circumstances. The objectives of a robust face recognition system is given below.
Scale Invariance. The same face can be presented to the system at different scales . This may happen due to the focal distance between the face and the camera. As this distance gets closer, the face image gets bigger.
Shift invariance. The same face can be presented to the system at different perspectives and orientations. For instance, face images of the same person could be taken from frontal and profile views. Besides, head orientation may change due to translations and orientations.
Illumination Invariance. Face images of the same person can be taken under different illumination conditions such as, the position and strength of the light source can be modified.
Emotional and Detail Invariance. Face images of the same person can differ in expressions when smiling and laughing. some details such as dark glasses, beards or moustaches can be present.
A SURVEY ON FACE RECOGNITION METHODS
There are three major research groups which propose three different approaches to the face recognition problem. The largest group has dealt with facial characteristics which are used by human beings in recognizing individual faces. The second group performs human face identification based on feature vectors extracted from profile silhouettes. The third group uses feature vectors extracted from a frontal view of the face. Although there are three different approaches to the face recognition problem, there are two basic methods from which these three different approaches arise.
The first method is based on the information theory concepts, in other words, on the principal component analysis methods. In this approach, the most relevant information that best describes a face is derived from the entire face image. Based on the Karhunen-Loeve expansion in pattern recognition, M. Kirby and L. Sirovich have shown that any particular face could be economically represented in terms of a best coordinate system that they termed "eigenfaces". These are the eigen functions of the averaged covariance of the ensemble of faces. Later, M. Turk and A. Pentland have proposed a face recognition method based on the eigenfaces approach.
HUMAN RECOGNITION
Within today’s environment of increased importance of security and organization, identification and authentication methods have developed into a key technology in various areas: entrance control in buildings; access control for computers in general or for automatic teller machines in particular; day-to-day affairs like withdrawing money from a bank account or dealing with the post office; or in the prominent field of criminal investigation. Such requirement for reliable personal identification in computerized access control has resulted in an increased interest in biometrics.
Biometric identification is the technique of automatically identifying or verifying an individual by a physical characteristic or personal trait. The term “automatically” means the biometric identification system must identify or verify a human characteristic or trait quickly with little or no intervention from the user. Biometric technology was developed for use in high-level security systems and law enforcement markets. The key element of biometric technology is its ability to identify a human being and enforce security.
CONCLUSION
A complete literature survey on face recognition system has been done in this chapter along with other feature based methods. Commonly used image based methods gives a better recognition rate than feature based methods.