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Claims  |
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We claim:
1. In a system including an imager having a lens for deriving a focused
image of an eye of a user of the system; the improvement comprising:
alignment means for permitting said user to self-position his or her eye
into said imager's field of view without the need for any physical contact
with said system, said alignment means comprises:
(a) first edge means having a given outline contour shape of a first given
size that is substantially centered with respect to said lens, said first
edge means being disposed a first distance in front of said lens; and
(b) second edge means having an outline contour shape of a second given
size smaller than said first given size that is geometrically similar in
shape to said given outline contour shape and is substantially centered
with respect to said lens, said second edge means being disposed a second
distance in front of said lens that is longer than said first distance by
a specified amount, said specified amount being such that said lens forms
a focused image of said user's eye when said user's eye is maneuvered to a
point in space in front of said lens at which said outline contour of said
first edge means is substantially totally occluded by said outline contour
of said second edge means as viewed by said user's eye from the point.
2. The system of claim 1, wherein:
said given outline contour shape of said first edge means is square;
whereby said geometrically similar outline contour shape of said second
edge means is also square.
3. The system of claim 1, wherein said system further comprises:
light means for illuminating said user's eye with diffuse light which is
circularly polarized in a given sense of rotation to derive diffusely
reflected light from said user's eye that is incident on said lens.
4. The system of claim 3, wherein said light means comprises:
an array of light sources which surround said imager for deriving
illuminating light;
a diffuser panel through which said illuminating light from said array of
light sources passes prior to reflection from the user's eye, said
diffuser panel having a hole therein situated with respect to said lens
for permitting said reflected light to reach said lens without passing
through said diffuser panel; and
a circular polarizer situated in front of said diffuser panel and said lens
for circularly polarizing the illuminating light reaching said user's eye
in said given sense of rotation.
5. The system of claim 3, further comprising:
a digital frame grabber coupled to said imager for deriving digital data
representative of said focused image of said eye of a user.
6. The system of claim 1, wherein said imager is a relatively
high-resolution, narrow-field imager and said alignment means further
comprises:
a relatively low-resolution, wide field imager for deriving successive
video frames of image information that includes predetermined facial
features of said user;
image processing means responsive to said predetermined-facial-feature
image information for locating the position of said user's eye in said
video frames thereof; and
means associated with said image processing means which is responsive to
the location of the position of said user's eye in said video frames of
said low-resolution, wide field imager for permitting said
high-resolution, narrow field imager to be provided with a focused image
of said user's eye.
7. The system of claim 6, wherein:
said means associated with said image processing means includes an active
mirror positioned in accordance with said located position of said user's
eye in said video frames of said relatively low-resolution, wide field
imager.
8. The system of claims 6, wherein said imaging processing means includes:
a Gaussian pyramid for deriving a multistage image pyramid of at least one
of said successive video frames of image information; and
means responsive to said image-pyramid stages for deriving a change energy
pyramid.
9. In a system including an imager having a lens for deriving a focused
image of an eye of a user of the system to examine the iris of said user's
eye, the improvement comprising:
alignment means for permitting said user to self-position his or her eye
into said imager's field of view without the need for any physical contact
with said system;
a digital frame grabber coupled to said imager for deriving digital data
representative of said focused image of said user's eye;
image processing means responsive to the digital data from said frame
grabber that manifests said user's eye for localizing the iris of said eye
by, in sequential order, (1) locating that data which is within the image
of the user's eye that defines the limbic boundary of said iris, (2)
locating that data which is within said limbic boundary that defines the
pupilary boundary of said iris, (3) locating that data which is within
said limbic boundary that defines the boundaries of the upper and lower
eyelids of said eye, and (4) then employing that data that is outside of
said pupilary boundary, inside said limbic boundary, and below the upper
eyelid and above the lower eyelid thereby to delimit said data to that
portion thereof which manifests the iris of said eye, the image processing
means comprising:
(a) gradient-based edge detector filter means tuned in orientation to favor
near verticality for deriving detected edge data; and
(b) means, responsive to said limbic boundary being modeled as a circle
parameterized by its two center coordinates, xc and yc, and its radius, r,
for thinning and then histogramming said detected edge data into a
three-dimensional (xc, yc, r)-space, according to permissible (xc, yc, r)
values for a given (x, y) image location; whereby the (xc, yc, r) point
with the maximal number of votes is taken to represent the limbic
boundary.
10. In a system including an imager having a lens for deriving a focused
image of an eye of a user of the system to examine the iris of said user's
eye, the improvement comprising:
alignment means for permitting said user to self-position his or her eye
into said imager's field of view without the need for any physical contact
with said system;
a digital frame grabber coupled to said imager for deriving digital data
representative of said focused image of said user's eye;
image processing means responsive to the digital data from said frame
grabber that manifests said user's eye for localizing the iris of said eye
by, in sequential order, (1) locating that data which is within the image
of the user's eye that defines the limbic boundary of said iris, (2)
locating that data which is within said limbic boundary that defines the
pupilary boundary of said iris, (3) locating that data which is within
said limbic boundary that defines the boundaries of the upper and lower
eyelids of said eye, and (4) then employing that data that is outside of
said pupilary boundary, inside said limbic boundary, and below the upper
eyelid and above the lower eyelid thereby to delimit said data to that
portion thereof which manifests the iris of said eye, the image processing
means comprising:
(a) gradient-based edge detector filter means that is directionally untuned
in orientation for deriving detected edge data; and
(b) means, responsive to said pupilary boundary being modeled as a circle
parameterized by its two center coordinates, xc and yc, and its radius, r,
for thinning and then histogramming said detected edge data into a
three-dimensional (xc, yc,r)-space, according to permissible (xc, yc,r)
values for a given (x, y) image location;
whereby the (xc, yc, r) point with the maximal number of votes is taken to
represent the pupilary boundary.
11. In a system including an imager having a lens for deriving a focused
image of an eye of a user of the system to examine the iris of said user's
eye, the improvement comprising:
alignment means for permitting said user to self-position his or her eye
into said imager 's field of view without the need for any physical
contact with said system;
a digital frame grabber coupled to said imager for deriving digital data
representative of said focused image of said user's eye;
image processing means responsive to the digital data from said frame
grabber that manifests said user's eye for localizing the iris of said eye
by, in sequential order, (1) locating that data which is within the image
of the user's eye that defines the limbic boundary of said iris, (2)
locating that data which is within said limbic boundary that defines the
pupilary boundary of said iris, (3) locating that data which is within
said limbic boundary that defines the boundaries of the upper and lower
eyelids of said eye, and (4) then employing that data that is outside of
said pupilary boundary, inside said limbic boundary, and below the upper
eyelid and above the lower eyelid thereby to delimit said data to that
portion thereof which manifests the iris of said eye, the image processing
means comprising:
(a) gradient-based edge detector filter means tuned in orientation to favor
the horizontal for deriving detected edge data; and
(b) means, responsive to each of said upper eyelid boundary and said lower
eyelid boundary of said eye being modeled as a parabolic parameterized by
second-order arcs, in which particular values for the parameterization are
instantiated by thinning and then histogramming said detected edge data
into a three-dimensional space, according to permissible values for a
given image location;
whereby the spatial point with the maximal number of votes is taken to
represent that eyelid boundary.
12. In a system directed to automated iris recognition for security access
control including (1) an imager having a lens for deriving a focused image
of an eye of a user of the system and (2) a digital frame grabber coupled
to said imager for deriving digital data representative of said focused
image of said user's eye, the improvement comprising:
alignment means for permitting said user to self-position his or her eye
into the field of view of said imager without the need for any physical
contact with said system; and
image processing means including:
(a) iris-localizing means responsive to digital data from said frame
grabber that manifests said user's eye for substantially delimiting said
digital data to only that portion thereof which manifests solely the iris
of said user's eye; and
(b) pattern-matching means, responsive to said portion of said digital data
and previously stored digital data which manifests solely the iris of an
eye of a given individual, said pattern-matching means employing
normalized spatial correlation, for:
(1) first comparing, at each of a plurality of spatial scales, each of
distinctive spatial characteristics of the respective irises of said user
and said given individual that are spatially registered with one another
to quantitatively determine, at each of said plurality of spatial scales,
a goodness value of match at that spatial scale, and then
(2) judging whether or not the pattern of said delimited digital data which
manifests solely said iris of said user's eye matches said digital data
which manifests solely the iris of the eye of said given individual in
accordance with a certain combination of the quantitatively-determined
goodness values of match at each of said plurality of spatial scales,
the pattern matching means comprising:
area-based image registration means utilizing a mapping function
(u(x,y),v(x,y)) constrained to be a similarity transformation of
translational shift, scale and rotation, such that, for all (x,y), the
data value at (x,y)-(u(x,y),v(x,y)) in the delimited digital data which
manifests solely said iris of said user's eye is close to that at (x,y) of
said digital data which manifests solely the iris of the eye of said given
individual.
13. In a system directed to automated iris recognition for security access
control including (1) an imager having a lens for deriving a focused image
of an eye of a user of the system and (2) a digital frame grabber coupled
to said imager for deriving digital data representative of said focused
image of said user's eye, the improvement comprising:
alignment means for permitting said user to self-position his or her eye
into field of view of said imager without the need for any physical
contact with said system; and
image processing means including:
(a) iris-localizing means responsive to digital data from said frame
grabber that manifests said user's eye for substantially delimiting said
digital data to only that portion thereof which manifests solely said iris
of said user's eye; and
(b) pattern-matching means, responsive to said portion of said digital data
and previously stored digital data which manifests solely the iris of an
eye of a given individual, said pattern-matching means employing
normalized spatial correlation, for:
(1) first comparing, at each of a plurality of spatial scales, each of
distinctive spatial characteristics of the respective irises of said user
and said given individual that are spatially registered with one another
to quantitatively determine, at each of said plurality of spatial scales,
a goodness value of match at that spatial scale, and then
(2) judging whether or not the pattern of said delimited digital data which
manifests solely said iris of said user's eye matches said digital data
which manifests solely the iris of the eye of said given individual in
accordance with a certain combination of the quantitatively-determined
goodness values of match at each of said plurality of spatial scales,
the pattern matching means comprising:
means for combining the quantitatively-determined goodness values of match
at each of said plurality of spatial scales so that the variance within
various instances of the same iris is minimized and the variance within
various instances of different irises is maximized.
14. The system of claim 13, wherein:
said means for combining the quantitatively-determined goodness values of
match at each of said plurality of spatial scales employs Fisher's Linear
Discriminant as a linear function that minimizes the variance among
various instances of the same iris and maximizes the variance among
various instances of different irises.
15. In an image-processing method responsive to digital data defining a
digitized image of the eye of an individual for delimiting said digital
data to that portion thereof that defines the iris of said eye of said
individual to the relative exclusion of other components of the eye of the
individual, said method comprising the steps of:
a delimiting step of locating that data which is within the image of said
individual's eye that define the limbic boundary of said iris, the
pupilary boundary of said iris, and the boundaries of the upper and lower
eyelids of said eye, the delimiting step includes the sequential steps of:
(a) first, locating that portion of said digital data that defines the
limbic boundary of said iris, step (a) includes the steps of:
(i) employing gradient-based edge detector filter means tuned in
orientation to favor near verticality for detecting edge data; and
(ii) thinning and then histogramming said detected edge data into a
three-dimensional (xc, yc, r)-space, according to permissible (xc, yc, r)
values for a given (x, y) image location in accordance with a model of
said limbic boundary as a circle parameterized by its two center
coordinates, xc and yc, and its radius r, the histogramming step embodies
a voting scheme which produces votes for recovering said limbic boundary;
whereby the (xc, yc, r) point with the maximal number of the votes is
taken to represent the limbic boundary;
(b) second, locating that portion of said digital data which is within said
limbic boundary that defines the pupilary boundary of said iris;
(c) third, locating that portion of said digital data which is within said
limbic boundary that defines the boundaries of the upper and lower eyelids
of said eye; and
(d) fourth, employing only that portion of said digital data that is
outside of said pupilary boundary, inside said limbic boundary, and below
the upper eyelid and above the lower eyelid thereby to delimit said
digital data to that portion thereof which manifests said iris of said
eye;
the delimiting step further includes the steps of:
(e) image-filtering said one of the limbic boundary of said iris, the
pupilary boundary of said iris, and the boundaries of said upper and lower
eyelids to derive an enhanced image thereof; and
(f) histogramming said enhanced image, in which said histogramming step
embodies the voting scheme for recovering one of the boundaries of the
iris from said enhanced image;
whereby said recovery of said one of the boundaries of said iris does not
require knowledge of any initial conditions other than the digital data
defining said digitized image of said eye of said individual.
16. In an image-processing method responsive to digital data defining a
digitized image of the eye of an individual for delimiting said digital
data to that portion thereof that defines the iris of said eye of said
individual to the relative exclusion of other components of the eye of the
individual; said method comprising the steps of:
a delimiting step of locating that data which is within the image of said
individual's eye that define the limbic boundary of said iris, the
pupilary boundary of said iris, and the boundaries of the upper and lower
eyelids of said eye, the delimiting step includes the sequential steps of:
(a) first, locating that portion of said digital data that defines the
limbic boundary of said iris;
(b) second, locating that portion of said digital data which is within said
limbic boundary that defines the pupilary boundary of said iris;
(c) third, locating that portion of said digital data which is within said
limbic boundary that defines the boundaries of the upper and lower eyelids
of said eye; and
(d) fourth, employing only that portion of said digital data that is
outside of said pupilary boundary, inside said limbic boundary, and below
the upper eyelid and above the lower eyelid thereby to delimit said
digital data to that portion thereof which manifests said iris of said
eye, step (d) includes the steps of:
(i) employing gradient-based edge detector filter means that is
directionally untuned in orientation for detecting edge data; and
(ii) thinning and then histogramming said detected edge data into a
three-dimensional (xc, yc, r)-space, according to permissible (xc, yc, r)
values for a given (x, y) image location in accordance with a model of
said pupilary boundary as a circle parameterized by its two center
coordinates, xc, and yc, and its radius r, the histogramming step embodies
a voting scheme which produces votes for recovering said limbic boundary;
whereby the (xc, yc, r) point with the maximal number of the votes is taken
to represent the pupilary boundary;
the delimiting step further includes the steps of:
(e) image-filtering said one of the limbic boundary of said iris, the
pupilary boundary of said iris, and the boundaries of said upper and lower
eyelids to derive an enhanced image thereof; and
(f) histogramming said enhanced image, in which said histogramming step
embodies the voting scheme for recovering one of the boundaries of the
iris from said enhanced image;
whereby said recovery of said one of the boundaries of the iris does not
require knowledge of any initial conditions other than the digital data
defining said digitized image of said eye of said individual.
17. In an image-processing method responsive to digital data defining a
digitized image of an eye of an individual for delimiting said digital
data to that portion thereof that defines solely the iris of said eye of
said individual; wherein said method includes a delimiting step of
locating that data which is within the image of said individual's eye that
defines at least one of the limbic boundary of said iris, the pupilary
boundary of said iris, and the boundaries of upper and lower eyelids of
said eye; said delimiting step comprising the steps of:
a) image-filtering said one of the limbic boundary of said iris, the
pupilary boundary of said iris, and the boundaries of said upper and lower
eyelids to derive an enhanced image thereof;
b) histogramming said enhanced image, in which said histogramming step
embodies a voting scheme for recovering said one of said iris boundaries
from said enhanced image;
said delimiting step further including the sequential steps of:
c) first, locating that portion of said digital data that defines said
limbic boundary of said iris;
d) second, locating that portion of said digital data which is within said
limbic boundary that defines said pupilary boundary of said iris;
e) third, locating that portion of said digital data which is within said
limbic boundary that defines said boundaries of said upper and lower
eyelids of said eye by:
(1) employing gradient-based edge detector filter means tuned in
orientation to favor the horizontal for detecting edge data; and
(2) thinning and then histogramming said detected edge data into a
three-dimensional space, according to permissible values for a given image
location in accordance with a model of each of the upper eyelid boundary
and the lower eyelid boundary as a parabolic parameterized by second-order
arcs;
whereby the spatial point with the maximal number of votes is taken to
represent that eyelid boundary; and
f) fourth, employing only that portion of said digital data that is outside
of said pupilary boundary, inside said limbic boundary, and below the
upper eyelid and above the lower eyelid thereby to delimit said digital
data to that portion thereof which manifests the iris of the eye;
whereby said recovery of said one of said iris boundaries does not require
knowledge of any initial conditions other than the digital data defining
said digitized image of said eye of said individual.
18. In an image-processing method for use in providing automated iris
recognition for security access control; said method being responsive to
first digital data defining a digitized image of the iris of the eye of a
certain individual to the relative exclusion of other components of the
eye of the certain individual attempting access and previously stored
second digital data of a digitized image that defines the iris of the eye
of a specified individual to the relative exclusion of other components of
the eye of the specified individual; said method comprising the steps of:
a pattern-matching step which comprises the steps of:
a) employing normalized spatial correlation for first comparing, at each of
a plurality of spatial scales, each of distinctive spatial characteristics
of the respective irises of said given individual and said specified
individual that are spatially registered with one another to
quantitatively determine, at each of said plurality of spatial scales, a
goodness value of match at that spatial scale; and
b) judging whether or not the pattern of said digital data which manifests
said iris of said eye of said given individual matches said digital data
which manifests the iris of an eye of said specified individual in
accordance with a certain combination of the quantitatively-determined
goodness values of match at each of said plurality of spatial scales.
19. In an image-processing method for use in providing automated iris
recognition for security access control; said method being responsive to
first digital data defining a digitized image of solely the iris of the
eye of a certain individual attempting access and previously stored second
digital data of a digitized image that defines solely the iris of the eye
of a specified individual; said method comprising the steps of:
a pattern-matching step which comprises the steps of:
a) employing normalized spatial correlation for first comparing, at each of
a plurality of spatial scales, each of distinctive spatial characteristics
of the respective irises of said given individual and said specified
individual that are spatially registered with one another to
quantitatively determine, at each of said plurality of spatial scales, a
goodness value of match at that spatial scale, where step a) comprises the
step of:
employing area-based image registration utilizing a mapping function
(u(x,y),v(x,y)) constrained to be a similarity transformation of
translational shift, scale and rotation, such that, for all (x,y), the
data value at (x,y)-(u(x,y),v(x,y)) in the first digital data which
manifests solely said iris of said eye of said given individual is close
to that at (x,y) of said second digital data which manifests solely the
iris of the eye of said specified individual;
b) judging whether or not the pattern of said digital data which manifests
solely said iris of said eye of said given individual matches said digital
data which manifests solely the iris of an eye of said specified
individual in accordance with a certain combination of the
quantitatively-determined goodness values of match at each of said
plurality of spatial scales.
20. The method of claim 18, wherein step (a) comprises the step of:
c) performing normalized spatial correlation over given spatial blocks made
up of a first plurality of data points in a first spatial dimension of
each of said plurality of scales and a second plurality of data points in
a second spatial dimension of each of said plurality of scales.
21. The method of claim 20, wherein step (c) comprises the step of:
d) combining said normalized spatial correlation over said given spatial
blocks via a median statistic at each of said plurality of spatial scales
for quantitatively determining said goodness value of match at that
spatial scale.
22. In an image-processing method for use in providing automated iris
recognition for security access control; said method being responsive to
first digital data defining a digitized image of solely the iris of the
eye of a certain individual attempting access and previously stored second
digital data of a digitized image that defines solely the iris of the eye
of a specified individual; said method comprising the steps of:
a pattern-matching step which comprises the steps of:
a) employing normalized spatial correlation for first comparing, at each of
a plurality of spatial scales, each of distinctive spatial characteristics
of the respective irises of said given individual and said specified
individual that are spatially registered with one another to
quantitatively determine, at each of said plurality of spatial scales, a
goodness value of match at that spatial scale;
b) judging whether or not the pattern of said digital data which manifests
solely said iris of said eye of said given individual matches said digital
data which manifests solely the iris of an eye of said specified
individual in accordance with a certain combination of the
quantitatively-determined goodness values of match at each of said
plurality of spatial scales by combining the quantitatively-determined
goodness values of match at each of said plurality of spatial scales so
that the variance within various instances of the same iris is minimized
and the variance within various instances of different irises is
maximized.
23. The method of claim 22, wherein step (c) comprises the step of:
d) employing Fisher's Linear Discriminant as a linear function that
minimized the variance among various instances of the same iris and
maximizes the variance amount various instances of different irises.
24. In a system directed to automated iris recognition for security access
control including (1) an imager having a lens for deriving a focused image
of an eye of a user of the system and (2) a digital frame grabber coupled
to said imager for deriving digital data representative of said focused
image of said user's eye, the improvement comprising:
alignment means for permitting said user to self-position his or her eye
into said imager's field of view without the need for any physical contact
with said system; and
image processing means including:
(a) iris-localizing means responsive to digital data from said frame
grabber that manifests said user's eye for substantially delimiting said
digital data to only that portion thereof which manifests said iris of
said user's eye to the relative exclusion of other components of the
user's eye; and
(b) pattern-matching means, responsive to said portion of said digital data
and previously stored digital data which manifests the iris of an eye of a
given individual to the relative exclusion of other components of the eye
of the individual, said pattern-matching means employing normalized
spatial correlation, for:
(1) first comparing, at each of a plurality of spatial scales, each of
distinctive spatial characteristics of the respective irises of said user
and said given individual that are spatially registered with one another
to quantitatively determine, at each of said plurality of spatial scales,
a goodness value of match at that spatial scale, and then
(2) judging whether or not the pattern of said delimited digital data which
manifests said iris of said user's eye matches said digital data which
manifests the iris of the eye of said given individual in accordance with
a certain combination of the quantitatively-determined goodness values of
match at each of said plurality of spatial scales.
25. The system of claim 1, further comprising an imaging path between the
imager and the user's eye, wherein the first edge means and the second
edge means are positioned outside of the imaging path.
26. In a system directed to automated iris recognition for security access
control including (1) an imager having a lens for deriving a focused image
of an eye of a user of the system and (2) a digital frame grabber coupled
to said imager for deriving digital data representative of said focused
image of said user's eye, the improvement comprising:
image processing means including:
(a) iris-localizing means responsive to digital data from said frame
grabber that manifests said user's eye for substantially delimiting said
digital data to that portion thereof which manifests said iris of said
user's eye to the relative exclusion of other components of the user's
eye; and
(b) pattern-matching means, responsive to said portion of said digital data
and previously stored digital data which manifests the iris of an eye of a
given individual to the relative exclusion of other components of the eye
of the given individual, said pattern-matching means employing normalized
spatial correlation, for:
(1) first comparing, at each of a plurality of spatial scales, each of
distinctive spatial characteristics of the respective irises of said user
and said given individual that are spatially registered with one another
to quantitatively determine, at each of said plurality of spatial scales,
a goodness value of match at that spatial scale, and then
(2) judging whether or not the pattern of said delimited digital data which
manifests said iris of said user's eye matches said digital data which
manifests the iris of the eye of said given individual in accordance with
a certain combination of the quantitatively-determined goodness values of
match at each of said plurality of spatial scales,
the pattern matching means comprising:
area-based image registration means utilizing a mapping function
(u(x,y),v(x,y)) constrained to be a similarity transformation of
translational shift, scale and rotation, such that, for all (x,y), the
data value at (x,y)-(u(x,y),v(x,y)) in the delimited digital data which
manifests said iris of said user's eye is close to that at (x,y) of said
digital data which manifests the iris of an eye of said given individual.
27. In a system directed to automated iris recognition for security access
control including (1) an imager having a lens for deriving a focused image
of an eye of a user of the system and (2) a digital frame grabber coupled
to said imager for deriving digital data representative of said focused
image of said user's eye, the improvement comprising:
image processing means including:
(a) iris-localizing means responsive to digital data from said frame
grabber that manifests said user's eye for substantially delimiting said
digital data to only that portion thereof which manifests said iris of
said user's eye to the relative exclusion of other components of the
user's eye; and
(b) pattern-matching means, responsive to said portion of said digital data
and previously stored digital data which manifests the iris of an eye of a
given individual to the relative exclusion of other components of the eye
of the given individual, said pattern-matching means employing normalized
spatial correlation, for:
(1) first comparing, at each of a plurality of spatial scales, each of
distinctive spatial characteristics of the respective irises of said user
and said given individual that are spatially registered with one another
to quantitatively determine, at each of said plurality of spatial scales,
a goodness value of match at that spatial scale, and then
(2) judging whether or not the pattern of said delimited digital data which
manifests said iris of said user's eye matches said digital data which
manifests the iris of the eye of said given individual in accordance with
a certain combination of the quantitatively-determined goodness values of
match at each of said plurality of spatial scales,
the pattern matching means comprising:
means for combining the quantitatively-determined goodness values of match
at each of said plurality of spatial scales so that the variance within
various instances of the same iris is minimized and the variance within
various instances of different irises is maximized.
28. In an image-processing method responsive to digital data defining a
digitized image of an eye of an individual for delimiting said digital
data to that portion thereof that defines the iris of said eye of said
individual to the relative exclusion of other components of the eye of
said individual; wherein said method includes a delimiting step of
locating that | | |
