IRIS/RETINA BIOMETRICS CPSC 4600@UTC/CSE

1. IRIS/RETINA BIOMETRICSCPSC 4600@UTC/CSE

2. RETINA/IRIS BIOMETRICS • Biometrics which analyze the complex and unique characteristics of the eye can be divided into two different fields: • iris biometrics - iris is the colored band of tissue that surrounds the pupil of the eye. • retina biometrics - retina is the layer of blood vessels at the back of the eye.

3. Iris Recognition

4. Understanding Iris Recognition • The iris is the area of the eye where the pigmented or colored circle, usually brown or blue, rings the dark pupil of the eye. • Iris scan biometrics employs the unique characteristics and features of the human iris in order to verify the identity of an individual. • An iris recognition system uses a video camera to capture the sample while the software compares the resulting data against stored templates.

5. Iris • The round opening in the center of the iris is called the pupil. The iris is embedded with tiny muscles that dilate (widen) and constrict (narrow) the pupil size. • The sphincter muscle lies around the very edge of the pupil. In bright light, the sphincter contracts, causing the pupil to constrict. The dilator muscle runs radically through the iris, like spokes on a wheel. This muscle dilates the eye in dim lighting. • The iris is flat and divides the front of the eye (anterior chamber) from the back of the eye (posterior chamber). Its color comes from microscopic pigment cells called melanin. • The color, texture, and patterns of each person's iris are as unique as a fingerprint. http://www.stlukeseye.com/anatomy/Iris.asp

6. Anatomy of the eye

7. Iris • Iris is the annular region of the eye responsible for controlling and directing light to the retina. It is bounded by the pupil and the sclera (white of the eye); iris is small (11 mm) • • Visual texture of the iris stabilizes during the first two years of life and carries distinctive information useful for identification • • Each iris is unique; even irises of identical twins are different

8. Advantages off Iris for Recognition • Believed to be stable over a person’s lifetime • Pattern is epigenetic (not genetically determined) • Internal organ, highly protected and rarely damaged or changed • Iris patterns possess a high degree of randomness • Imaging procedure is non-invasive • Template size is small • Image encoding and matching process is fast.

9. Stability of Iris Pattern The iris begins to form in the third month of gestation, and the trabecular meshwork creating its pattern are largely complete by the eighth month. Pigment accretion can continue into the first postnatal years. Iris color is determined mainly by the density of melanin pigment. Blue irises result from an absence of pigment. “The available clinical evidence indicates that the trabecular pattern itself is stable throughout the lifespan.”

10. Iridology “Throughout the ages, the eyes have been known as the windows to the soul, and modern behavioral research is proving this adage to be true. If you look closely at the iris of the eye, you will notice small, dark dots, light streaks or rounded openings in the fibers. These characteristics provide the key to unlocking the mysteries of the personality” (Rayid International).

11. Iridology • There is a popular belief in systematic changes in the iris pattern, reflecting the state of health of each of the organs in the body, one's mood or personality, and revealing one's future. • Iridology resembles palm-reading and is popular in parts of Romania and in California (According to Daugman). • “All scientific tests dismiss iridology as a medical fraud”– Berggren, L. (1985), “Iridology: A critical review”, Acta Ophthalmologica, 63(1): 1-8

12. Iris under different lighting • Visible Light • Layers visible • Less texture information • Melanin absorbs visible light • Infrared Light • Melanin reflects most infrared light • More texture is visible • Preferred for iris recognition systems

13. Infrared Iris Image In infrared light, even dark brown eyes show rich iris texture

14. Iris Capturing Devices • Different Cameras available: • – Hand held • – Wall mounted

15. Deployment of Iris Recognition • The largest deployment of iris recognition systems is in the United Arab Emirates (17 air, land, and sea ports). • 3.8 billion comparisons are conducted each day; average time per match is only a fraction of a second.

16. Frequent Flyers (belonging to EU) are enrolled in the "Privium“ program at Schiphol Airport (NL), enabling them to enter The Netherlands without presenting their passports .

17. • German Chancellor Gerhard Schroeder tests the iris recognition system used for automated passport control at Frankfurt's international airport, Europe's largest, in August 2004. • Up to 100 passengers use the service each day to bypass lengthy lines at regular security checkpoints.

18. Condominium residents in Tokyo gain entry to the building using iris patterns, and the elevator is automatically called and programmed to bring them to their residential floor.

19. The United Nations High Commission for Refugees administers cash grants to refugees returning to Afghanistan from surrounding countries after the fall of the Taleban, using iris patterns in lieu of any other forms of identification. More than 350,000 persons have so far been processed by this program using iris recognition.

20. Iris Representation Schema • Daugman • Gabor Demodulation (PAMI 1993) • Lim, Lee, Byeon, Kim • Wavelet Features (ETRIJ 2001) • Bae, Noh, Kim • Independent Component Analysis (AVBPA 2003) • Ma, Tan, Wang, Zhang • Key local variations (IEEE TIP 2004)

21. Daugman’s Approach • J. Daugman, “Statistical Richness of Visual Phase Information: Update on Recognizing Persons by Iris Patterns”, International Journal of Computer Vision, 2001. • J. Daugman, “Biometric Personal Identification System Based On Iris Analysis”, US Patent 5291560, 1994

22. Iris Localization- Curvilinear Boundaries

23. Detected Curvilinear Boundaries

24. Intra-class Variations Inconsistent Iris Size (distance from the camera) Pupil Dilation (lighting changes) Eye Rotation (head tilt)

25. Establishing Coordinate SystemDaugman’s Rubber Sheet Model Centers of iris and pupil coincide Centers of iris and pupil do not coincide The model remaps each point within the iris region to a pair of polar coordinates (r,θ) where r is in the interval [0,1] and θ is angle in [0,2π] • The model compensates pupil dilation and size inconsistencies by producing a size- and translation-invariant representation in the polar coordinate system • • The model does not compensate for rotational inconsistencies, which is accounted for during matching by shifting the iris templates in the θ direction until two iris templates are aligned.

26. Iris Feature Encoding odd symmetric even symmetric

27. A 1D illustration of the encoding process A total of 2,048 bits, i.e. 256 bytes of information is extracted from the whole iris image John Daugman’s personal website: http://www.cl.cam.ac.uk/users/jgd1000/

28. Example of Iris Coding Image size is 64 x 256 bytes and the iris code is 8 x 32 bytes; Gabor filter size is 8 x 8 Iris Patterns”, International Journal of Computer Vision, 2001.

29. Iris Code Matching • The comparison is done by computing the Hamming distance between two 256-byte iris codes • The Hamming Distance between an iris code X and another code Y is the sum of disagreeing bits (sum of the exclusive-OR between) divided by N, the total number of bits in the pattern. where N=2,048 (256 x 8) if there is no occlusion of the iris. Otherwise, only valid iris regions are used for computing the Hamming distance * Daugman, J. ,"High confidence visual recognition of persons by a test of statistical independence." IEEE Trans. on PAMI, 1993

30. Hamming distance • If two patterns are derived from the same iris, the Hamming distance between them will be close to 0.0 due to high correlation • In order to account for rotational inconsistencies, one template is shifted left and right bit-wise and a number of Hamming distance values are calculated from successive shifts. • The smallest Hamming distance is selected as it corresponds to the best match between two templates.

31. An illustration of iris matching by code shifting

32. Distribution of Hamming Distances amongUnrelated Iris Codes

33. Matching Score Distribution • The genuine and impostor Hamming distance distributions for about 2.3M comparisons • There is hardly any overlap and hence one can choose a threshold such that there is very small probability of error • This experiment shows that iris indeed is a very good biometric that can achieve very high performance. Matching Distance Distributions J. Daugman (1993) "High confidence visual recognition of persons by a test of statistical independence." IEEE Trans. PAMI, vol. 15(11), pp. 1148-1161.

34. http://www.cl.cam.ac.uk/users/jgd1000/

35. Limitations of Iris Limitations of Iris • Capturing an iris image involves cooperation from the user; user must stand at a predetermined distance and position in front of the camera • Cost of high performance iris systems is relatively high http://news.bbc.co.uk/1/hi/uk/1816221.stm

36. Limitations of Iris Limitations of Iris • Iris images may be of poor quality resulting in failures to enroll • In a recent test, up to 7% iris scans could still fail, due to anomalies such as watery eyes, long eyelashes or hard contact lenses. Occlusion (eyelids/eyelashes) Motion blurred Defocus Large pupil

37. Limitations of Iris • Iris can change over time (e.g., as a result of eye disease), leading to false rejects. • more than 200,000 cataract operations are performed each year in UK • about 60,000 people in UK have Nystagmus (tremor of the eyes) • about 1,000 people in UK have Anaridia (no iris) • Blind people may fail the test cataract surgery hyphaema(blood clot) iridodialysis

38. Anti-Spoofing Liveness Detection • Contact lens or photograph of a person's iris pattern can be used to spoof some iris recognition systems

39. The Live VS. Printed Iris The dot matrix printing process generates four points of spurious energy in the Fourier plane, corresponding to the directions and periodicities of coherence in the printing dot matrix, whereas anatural iris does not have these spurious coherences.

40. Effectiveness • The false acceptance rate for iris recognition systems is 1 in 1.2 million, statistically better than the average fingerprint recognition system. • The real benefit is in the false-rejection rate, a measure of authenticated users who are rejected. • Fingerprint scanners have a 3 percent false-rejection rate, whereas iris scanning systems boast rates at the 0 percent level • Eyeglasses and contact lenses present no problems to the quality of the image and the iris-scan systems test for a live eye by checking for the normal continuous fluctuation in pupil size.

41. Advantages of the Iris for Identification • Highly protected, internal organ of the eye • Externally visible; patterns imaged from a distance • Iris patterns possess a high degree of randomness • Changing pupil size confirms natural physiology • Limited genetic penetrance of iris patterns • Patterns apparently stable throughout life • Encoding and decision-making are tractable

42. Disadvantages of the Iris for Identification • Small target (1 cm) to acquire from a distance (1 m) • Moving target ...within another • Located behind a curved, wet, reflecting surface • Obscured by eyelashes, lenses, reflections • Partially occluded by eyelids, often drooping • Deforms non-elastically as pupil changes size • Illumination should not be visible or bright • Some negative (Orwellian) connotations

43. More about Iris Biometrics • Iris Recognition Systems, Systems, Evaluation, Surveys • http://www.visionbib.com/bibliography/people937e1.html

44. Retina

45. Retina • The retina is a thin layer of cells at the back of the eyeball of vertebrates. • It is the part of the eye which converts light into nervous signals. • The retina contains photoreceptor cells (rods and cones) which receive the light; the resulting neural signals then undergo complex processing by other neurons of the retina, and are transformed into action potentials in retinal ganglion cells whose axons form the optic nerve. • The retina not only detects light, it also plays a significant part in visual perception. • In embryonal development, the retina and the optic nerve originate as outgrowths of the brain. • The unique structure of the blood vessels in the retina has been used for biometric identification.

47. To brain Rods sense brightness Cones sense color The retina, in the back of your eye, has cells that are sensitive to light. They connect directly to your brain.

48. Retinal Recognition System (1) • Retina scans are performed by directing a low-intensity infrared light to capture the unique retina characteristics. • An area known as the face, situated at the center of the retina, is scanned  and the unique pattern of the blood vessels is captured. • Retina recognition technology captures and analyzes the patterns of blood vessels on the thin nerve on the back of the eyeball that processes light entering through the pupil. Retinal patterns are highly distinctive traits. • Every eye has its own totally unique pattern of blood vessels; even the eyes of identical twins are distinct. Although each pattern normally remains stable over a person’s lifetime, it can be affected by disease such as glaucoma, diabetes, high blood pressure, and autoimmune deficiency syndrome.

49. Retinal Recognition System (2) • Retina biometrics is considered to be one of the best biometric performers. • However, despite its accuracy, this technique is often thought to be inconvenient and intrusive. And so, it is difficult to gain general acceptance by the end user. • Eye and retinal scanner are ineffectual with the blind and those who have cataracts. • The fact that the retina is small, internal, and difficult to measure makes capturing its image more difficult than most biometric technologies. An individual must position the eye very close to the lens of the retina-scan device, gaze directly into the lens, and remain perfectly still while focusing on a revolving light while a small camera scans the retina through the pupil.

50. Retinal Recognition System (3) • Any movement can interfere with the process and can require restarting. Enrollment can easily take more than a minute. The generated template is only 96 bytes, one of the smallest of the biometric technologies. • It is one of the most accurate and most reliable of the biometric technologies, and it is used for access control in government and military environments that require very high security, such as nuclear weapons and research sites. • However, the great degree of effort and cooperation required of users has made it one of the least deployed of all the biometric technologies. Newer, faster, better retina recognition technologies are being developed.