IRIS RECOGNITION 1 CITY ENGINEERING COLLEGE Technical Seminar On “IRIS RECOGNITION” By NANDAN.T.MURTHY 1CE06EC043

IRIS RECOGNITION 2 Biometric System  A biometric system refers to automatic recognition of an individual based on their physiological and behavioral characteristics.  Physiological characteristics include physical characteristics like face,fingerprints,iris patterns etc.  Behavioral characteristics include signature, speech patterns etc.

What’s iris?  It is the colored portion (brown or blue) of the eye that regulates the size of the pupil.  The coloration and structure of two irides is genetically linked but the details of patterns are not.

IRIS RECOGNITION 4  They have stable and distinctive features for personal identification.  They are stable with age.  Extremely data rich physical structure about 400 identifying features.  Its inherent isolation and protection from the external environment.  The impossibility of surgically modifying it without unacceptable risk to vision. Why IRIS?

IRIS RECOGNITION 5 Individuality of Iris Left and right eye irises have distinctive pattern.

Iris Recognition System

IRIS RECOGNITION 7 I. Image Acquisition  It deals with capturing of a high quality image of the iris. Concerns on the image acquisition rigs :- –Obtain images with sufficient resolution and sharpness –Good contrast in the iris pattern with proper illumination –Well centered without unduly constraining the operator –Artifacts eliminated as much as possible

I. Image Acquisition  Distance up to 3 meter  Near-infrared camera or LED

ll. Iris localization  Iris localization is a process to isolate the iris region from the rest of the acquired image.  Iris can be approximated by two circles, One for iris/sclera boundary and another for iris/pupil boundary.

IRIS RECOGNITION 10 How localization is done? Pupil detection: circular edge detector I(x,y) eye image r is radius to search G(r) is Gaussian smoothing function s is contour of circle given by r,x,y

IRIS RECOGNITION 11 Normalization  Circular band is divided into 8 subbands of equal thickness for a given angle.  Subbands are sampled uniformly in and in r. Rubber Sheet Model Each pixel (x,y) is mapped into pair of polar coordinates (r, ). Where R is on interval (0,1) is angle (0,2pi)

IRIS RECOGNITION 12 Feature Encoding  Feature encoding was implemented by convolving the normalized iris pattern with 1D Log-Gober wavelet.  2D normalized patterns are broken up into a number of 1D signals  Each row corresponds to a circular ring on the iris region  The angular direction is taken rather than the radial one, which corresponds to columns of normalized pattern.

An illustration of the feature encoding process.

IRIS RECOGNITION March 24,  For matching, the Hamming distance was chosen as a metric for recognition.  The Daugman system computes the normalized Hamming distance. The hamming distance between iris code X and Y is given by: IV. Pattern Matching

IRIS RECOGNITION 15  The result of this computation is then used as the goodness of match, with smaller values indicating better matches.  If two patterns are derived from same iris,the hamming distance between them will be close to 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.

An illustration of the shifting process. One shift is defined as one shift left, and one shift right of a reference template. In this example one filter is used to encode the templates, so only two bits are moved during a shift. The lowest Hamming distance, in this case zero, is then used since this corresponds to the best match between the two templates.

IRIS RECOGNITION 17 Advantages of the Iris for Identification  Highly protected, internal organ of the eye.  Patterns apparently stable throughout life.  Iris patterns possess a high degree of randomness.  extremely data-rich physical structure.  Image analysis and encoding time: 1 second.  Search speed: 100,000 Iris Codes per second.

IRIS RECOGNITION 18 Disadvantages of the Iris for Identification  Small target (1 cm) to acquire from a distance (1 m)  Characteristic natural movement of an eyeball while text is read.  Obscured by eyelashes, lenses, reflections  Deforms non-elastically as pupil changes size  Illumination should not be visible or bright

Applications Current uses :- airports government agencies research laboratories In prisons Future uses :-  healthcare industry  Emigration services  sales transaction

IRIS RECOGNITION 20 Conclusion Based on the study we can conclude that iris recognition is one of the reliable and accurate biometric technology.

IRIS RECOGNITION March 24,