Retinal Scanning - Carnegie Mellon School of Computer Science

Retinal Scanning - Carnegie Mellon School of Computer Science

Retinal Scanning Biometrics Presentation by Ajinkya Bhave 30th April, 2003

Structure of the Eye What is the Retina? A very thin layer of tissue on the back of the eye (1/50 thick) Has rods and cones to sense light and colour

Transmits impulses through the optic nerve Multiple layers of cells comprise the retina Retina = CCD + DSP all in one Rods & Cones

The Technology Background One of the earliest biometric techniques early 1930s Very high level of accuracy (0.0001% FAR)

One of the most information-rich biometrics (over 400 feature points) Considered an intrusive technology Principle Identifies individuals by retinal blood vessel

pattern Unique for each individual (including twins) Patterns do not change over an individuals lifetime Exceptions include diabetes and macular degenerative diseases

Technique Subject looks into a focussing camera at close range (~ inch) for several seconds Low power IR (~7mW) is directed into the pupil Resulting picture is captured by the camera

May require several such images to get a good template Image processing filters out relevant feature points Pattern is matched against stored templates Commercial Systems

Only 2 currently in the market Widely differing hardware Widely differing price tags Eyedentify

System specifications Enrollment time : less than 1 minute ; Stand alone verification time : 1.5 seconds ; Stand alone recognition time. : less than 5 seconds with 1500 persons enrolled ;

Storage capacity : 3000 individuals in flash RAM memory Template size : 96 bytes Cost : $2000-$2500 Retinal Technologies

System specifications

Handheld device Variable capture distances ? upto 3 feet? Uses aspheric lens array to get this range

Laser opthalmoscope captures retinal image Template size : 50 bytes Estimated cost: ~ $200 Extracting Intensity Profile

Performing Scan Locating Blood Vessels Generating Circular Bar Code


Accuracy FAR rates as low as 0.0001% Stability of biometric sample Resistant to fraud Small template size large database on a small, standalone device

Comparison Chart Weaknesses Cumbersome to use practically Trained operative needed during operation Consumer perceptions (safety)

Cost (apparently not anymore with RT) Applications Security in Military areas Access-control Screening

Tracking livestock across regions (disease-spread prevention) Retinal Reflections ?

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