Iris Recognition SII

8/3/2019 Iris Recognition SII

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` Prashant Sarode

M.Tech II Year

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` Fingerprint recognition

` Face recognition

` Iris recognition

` Hand geometry measurement` Signature verification

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` In biometric technology first feature is capture then

it is transformed into some sort of mathematical

function into biometric template.

` This template is then compared with other

template in order to determine identity.

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` Iris recognition has two modes of operation

1] Enrolment mode :- add template to database.

2] Identification mode:-match is searched for database of pre-enrolled templates.

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` Iris is circular diaphragm between sclera and

pupil.

` Its function is to control the amount of light

entering through pupil.` The iris has a unique pattern on its surface.

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` Iris unique pattern remain stable throughout life.

` This unique pattern digitized and encode in to

biometric template.

` Biometric template contain mathematicalrepresentation of iris.

` It allows comparison to be made between

templates.

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` Segmentation- locating the iris region

` Normalization- create dimensionally consistent

representation of the iris region.

` Feature encoding and matching-create template

contain most discriminating feature of the iris.

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` It is first stage in iris recognition.

` It isolate actual iris region in digital image.

` Eye contain two circle iris/sclera boundary and

iris/pupil boundary.

` A technique required to locate the circular iris

region.

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` Hough transform is used to find lines and circle

present in an image.

` Circular Hough transform is used to detect radiusand centre coordinates of pupil and iris region.

` An edge map is generate by hough transform.

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` In horizontal direction it detect eyelid and in

vertical direction it detect outer circular boundary

of iris.

` Taking only vertical gradient for locating iris

boundary will reduce the influence of eyelid.

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` Normalisation:-Transformed the iris region in fixed

dimensions.

` Dimensional inconsistencies is due to pupil

dilation .` Varying imaging distance.

` Rotation of camera.

` Rotation of eye in eye socket.

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` Daugman¶s rubber sheet model is employed for

normalisation of iris region.

` Pupil centre is considered as reference point andradial vectors pass through the iris region.

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` Remapping the Cartesian coordinates to polar

` I (x(r,), y(r,)) I (r,)

` x (r,) = (1 ± r)xp() + rx1()` y (r,) = (1 ± r)yp() + ry1()

` Where I(x,y) is the iris region image ,(x,y)

cartesian coordinates and (r,) correspondingpolar coordinates. xp,yp and x1,y1 coordinates of pupil and iris boundaries along direction.

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` Thank You

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Documents

Iris Recognition SII