1. Introduction to Biometric Systems
Ruomu Guo
CSPC 620—Computer Security

2. Overview Identification Person’s body && identity
Applications: Fingerprint, Iris, Retina Recognition,
Face Detection, Hand Geometry.
Relationship between Biometric System and certain topics in the area of computer security.

3. Overview
Refers to the use of mathematical statistical methods to analyze biological behaviors or characteristics.
Biometric System mainly consists of four modules— Sensor, Feature Extraction, Matcher, System Database Storage.
Difficulties: Accuracy, Speed, Resource Requirements, Harmless to human beings, Robust to fraudulent attacks.

4. Measurement of Biometric System
Fig: The relationship between FAR, FRR, and Threshold Value

5. Fingerprint Recognition
Fingerprint Recognition, because of its lifetime invariance, uniqueness and convenience, is becoming an important method for biometric identification.
Finger skin ridge and valley forms a regular array of different pattern types. Valley, ridge combined with point and bifurcation point, are called the fingerprint minutiae points (minutiae).
By comparing different fingerprint minutiae, person’s identity can be recognized or identified.

6. Fingerprint Recognition
Fig: Block Diagram of Fingerprint Recognition Processes

7. Fingerprint Recognition
Sense: off-line fingerprint acquisition, live-scan sensing.
Feature Extraction: singular region, local ridge orientation
Matching: Correlation-based matching, Minutiae-based matching, Ridge feature-based matching
Database Storage: update periodically

8. Face Detection
Face Detection is also a popular method of biometric system for recognition and identifies individual’s identity.
Advantages: widely accept as a identifier, least intrusive.
Disadvantages: illumination, disguise for circumvention, and incompatible with pure identification protocol.

9. Face Detection Primary methods for detecting faces
1. Knowledge-based methods
2. Feature invariant approaches
3. Template matching methods
4. Appearance-based methods

10. Face Detection
The technique for face recognition can be classified as following three groups:
1. Feature Methods:
2. Holistic Methods:
3. Hybrid Methods:

11. PCA Application PCA (Principal Component Analysis)
A face image usually defines a point in the high- dimensional image space.
PCA is used to simplify the required process of analysis by reducing the dimensional spaces or subspaces.

12. Conclusion
Biometric System is not independent as a module for entire computer security area.
Some ticklish problems in computer security will be solved appropriately such as authentication for each person’s identity before they will enter or access to other systems.
Scientists are still trying to exploit other methods to improve the performance of biometric system with more enhancement of computer security.

13. Reference
1. A. K. Jain, A. Ross and S. Prabhakar, An Introduction to Biometric System IEEE Transactions on Circuits and Systems for Video Technology, Special Issue on Image- and Video-Based Biometrics, Vol. 14, No. 1, pp. 4-20, January 2004.
2. A. Jain, R. Bolle, and S. Pankanti, Introduction to Biometrics: Personal Identification in Networked Society (A. Jain, R. Bolle, and S. Pankanti, Eds. ), pp. 1-41, Boston, MA: Kluwer Academic, 1999.
3. D. Maltoni. A tutorial on Fingerprint Recognition: In M. Tistarelli, J. Bigun, and E. Grosso, editors, Biometrics School 2003, LNCS 3161, pages Springer Verlag, Berlin, Heidelberg, 2005.
4. Description of Face Detection at Wikipedia: