1. OUTLINE I.Biometrics: What Is It? II.Why Ear Biometrics? III.Ear Biometrics IV.How A Biometric System Works V.Conclusion

2. WHAT IS IT? Biometrics Physical as the face and hand behavioral as the read and writing

3. EAR BIOMETRICS BACKGROUND The science of establishing human identity based on the physical (e.g., fingerprints and iris) or be- havioral (e.g., gait) attributes of an individual is referred to as biometrics [Jain et al. 2004]. Humans have used body characteristics such as face and voice for thousands of years to recognize each other. In contemporary society, there is a pronounced interest in developing machine recognition systems that can be used for automated human recognition. With applications ranging from forensics to national security, biometrics is slowly becoming an integral part of modern society. The most common biometric systems are those based on characteristics that have been commonly used by humans for identification, such as fingerprint and face images, which have the largest market share. More re- cently, the iris biometric has been used in large-scale identity management systems such as border

4. EAR BIOMETRICS BACKGROUND The human ear is a new class of relatively stable biometrics. After decades of research of anthropomet- ric measurements of ear photographs of thousands of people, it has been found that no two ears are alike, even in the cases of identical and fraternal twins, triplets, and quadruplets [1]. It is also found that the structure of the ear does not change radically over time. Ear bio- metric has played a significant role in forensic science and its use by law enforcement agencies for many years [1] but most of this work has been on analyzing the ear prints manually. Recent work on ear biometrics focuses on developing automated techniques for ear recogni- tion [2]. Ear biometrics can be based on a 2D gray scale or color image, 3D range image, or a combination of 2D and 3D images. Typically, an ear biometric system consists of ear detection and ear recognition modules.

5. BIOMETRIC SYSTEM COMPONENTS Sensor Feature Extraction MatcherDATABASE

6. BIOMETRIC SYSTEM OPERATION VERIFICATION Identity Claimed One-to-one Comparison Authentication is either approved or denied. IDENTIFICATION No identity claimed One-to-many comparison Identity is determined User not being enrolled leads to fail of identification.

7. WHY EAR BIOMETRICS (FEATURES) Discourages fraud Enhances security Not Need Touch exactitude System Not Need employee To Make comparing Shape of Ear not be affected with advance Age

8. DEFECTS WAY Affected with obstruction Affected with perforation Affected with concentration Hair The Software not current Affected with lighting

9. EXAMPLES OF BAD AND GOOD IMAGES

10. CLARIFICATION

11. EAR BIOMETRICS APPROACHES Approaches  Global: Whole ear  Local: Sections of ear  Geometric: Measurements helix intertragic notch triangular fossa crus of helix tragus antitragus antihelix concha lobe

12. EAR BIOMETRICS APPROACHES

14. EAR SHAPE APPLICATIONS currently there are no applications, which use ear identification or authentication crime investigation is interested in using ear identification active ear authentication could be possible in different scenarios

15. APPLICATION SCENARIOS Application scenarios are quite traditional for biometrics: collecting child from daycare ATM any other active identification passive e.g. when trying to solve a crime and there’s a picture of ear in the tape of a surveillance camera e.g. gas station robbery in The Netherlands

16. CONCLUSION Ear recognition is still a relatively new area in biometrics research. Potential to be used in real-world applications to identify/authenticate humans by their ears. Can be used in both the low and high security applications and in combination with other biometrics such as face.

17. BY Tamer Farouk Eslam Mongey Under the supervision of Dr. Mina Ibrahim