IP Library Granted Patent US 11,126,879
Granted Patent B1
US 11,126,879 · App. 17/225,797 · Granted Sep 21, 2021

Spoof detection using illumination sequence randomization

Inventors: Spandana Vemulapalli (Kansas City, MO); David Hirvonen (Brooklyn, NY)
Assignee: EyeVerify, Inc.
G06K9/00906G06F17/11G06K9/00261G06K9/00295G06K9/4652G06K9/4661G06K9/6256G06N3/08
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Quick Facts
Patent No.
US 11,126,879
App. No.
17/225,797
Granted
Sep 21, 2021
Kind
B1
Abstract

Technology described herein includes a method that includes obtaining a set of color-coded sequences, each of which includes a sequence of colors. Each color-coded sequence has auto-correlation properties characterized by a merit factor larger than a first predetermined threshold, and cross-correlation properties among the color-coded sequences characterized by a demerit factor lower than a second predetermined threshold. A color-coded sequence is randomly selected from the set of color-coded sequences. A subject is illuminated in accordance with the sequence of colors in the selected color-coded sequence. A sequence of images of the subject are captured, and are temporally synchronized with illumination by the color-coded sequence. A filtered response image is generated from the sequence of images by a matched filtering process. Based on the filtered response image, it is determined that the subject is an alternative representation of a live person. In response, access to a secure system is prevented.

Claims (373)

1. A computer-implemented method comprising:

obtaining a set of multiple color-coded sequences, wherein each color-coded sequence comprises a sequence of colors, wherein each color-coded sequence has auto-correlation properties characterized by a merit factor larger than a first predetermined threshold, and cross-correlation properties among the color-coded sequences characterized by a demerit factor lower than a second predetermined threshold;

randomly selecting a color-coded sequence from the set of color-coded sequences;

illuminating a subject in accordance with the sequence of colors in the selected color-coded sequence;

capturing a sequence of images of the subject, wherein the sequence of images are temporally synchronized with illumination by the color-coded sequence;

generating, by a matched filtering process using the selected color-coded sequence, a filtered response image from the sequence of images of the subject;

determining, based on the filtered response image, that the subject is an alternative representation of a live person; and

responsive to determining that the subject is the alternative representation of the live person, preventing access to a secure system.

2. The method of claim 1 , wherein the alternative representation of the live person comprises a previously captured photograph of the live person printed on paper, or an image presented on a display device.

3. The method of claim 1 , wherein the alternative representation of the live person comprises video replay of the live person on a display device.

4. The method of claim 1 , wherein determining, based on the filtered response image, that the subject is the alternative representation of the live person comprises processing the filtered response image using a machine learning process trained to discriminate between filtered response images of live persons and filtered response images of alternative representations of the live persons.

5. The method of claim 1 , wherein generating, by the matched filtering process using the selected color-coded sequence, the filtered response image from the sequence of images of the subject comprises:

generating, from the sequence of images, a sequence of spatially aligned images;

calculating a sequence of filtered response images by applying a matched filter to the sequence of spatially aligned images, wherein the matched filter corresponds to the selected color-coded sequence; and

selecting the filtered response image from the sequence of filtered response images.

6. The method of claim 1 , wherein the merit factor is defined as:

d

=

1

M

C

f

,

f

(

0

,

d

)

2

s

!=

0

2

N

-

1

C

f

,

f

(

s

,

d

)

2

,

wherein M is a total number of colors in the color-coded sequence, N is length of the color-coded sequence, d is an index for the colors, C f,f is a one-dimensional discrete auto-correlation function of a color-coded sequence f, s is a correlation index in the function C f,f , and

wherein the demerit factor is defined as:

d

=

1

M

s

!=

0

2

N

-

1

C

f

,

g

(

s

,

d

)

2

C

f

,

f

(

0

,

d

)

·

C

g

,

g

(

0

,

d

)

,

wherein C g,g is a one-dimensional discrete auto-correlation of a color-coded sequence g, C f,g is a one-dimensional discrete cross-correlation of the color-coded sequence f and the color-coded sequence g.

7. The method of claim 1 , further comprising:

randomly selecting a second color-coded sequence from the set of color-coded sequences;

illuminating a second subject in accordance with the sequence of colors in the second color-coded sequence;

capturing a second sequence of images of the second subject, wherein the second sequence of images are temporally synchronized with illumination by the second color-coded sequence;

generating, by a matched filtering process using the second selected color-coded sequence, a second filtered response image from the second sequence of images of the second subject;

determining, based on the second filtered response image, that the second subject is a live person; and

responsive to determining that the second subject is the live person, initiating an authentication process for determining if the live person is authorized to access the secure system.

8. A computer-implemented system, comprising:

one or more computers; and

one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, perform operations comprising:

obtaining a set of multiple color-coded sequences, wherein each color-coded sequence comprises a sequence of colors, wherein each color-coded sequence has auto-correlation properties characterized by a merit factor larger than a first predetermined threshold, and cross-correlation properties among the color-coded sequences characterized by a demerit factor lower than a second predetermined threshold;

randomly selecting a color-coded sequence from the set of color-coded sequences;

illuminating a subject in accordance with the sequence of colors in the selected color-coded sequence;

capturing a sequence of images of the subject, wherein the sequence of images are temporally synchronized with illumination by the color-coded sequence;

generating, by a matched filtering process using the selected color-coded sequence, a filtered response image from the sequence of images of the subject;

determining, based on the filtered response image, that the subject is an alternative representation of a live person; and

responsive to determining that the subject is the alternative representation of the live person, preventing access to a secure system.

9. The computer-implemented system of claim 8 , wherein the alternative representation of the live person comprises a previously captured photograph of the live person printed on paper, or an image presented on a display device.

10. The computer-implemented system of claim 8 , wherein the alternative representation of the live person comprises video replay of the live person on a display device.

11. The computer-implemented system of claim 8 , wherein determining, based on the filtered response image, that the subject is the alternative representation of the live person comprises processing the filtered response image using a machine learning process trained to discriminate between filtered response images of live persons and filtered response images of alternative representations of the live persons.

12. The computer-implemented system of claim 8 , wherein generating, by the matched filtering process using the selected color-coded sequence, the filtered response image from the sequence of images of the subject comprises:

generating, from the sequence of images, a sequence of spatially aligned images;

calculating a sequence of filtered response images by applying a matched filter to the sequence of spatially aligned images, wherein the matched filter corresponds to the selected color-coded sequence; and

selecting the filtered response image from the sequence of filtered response images.

13. The computer-implemented system of claim 8 , wherein the merit factor is defined as:

d

=

1

M

C

f

,

f

(

0

,

d

)

2

s

!=

0

2

N

-

1

C

f

,

f

(

s

,

d

)

2

,

wherein M is a total number of colors in the color-coded sequence, N is length of the color-coded sequence, d is an index for the colors, C f,f is a one-dimensional discrete auto-correlation function of a color-coded sequence f, s is a correlation index in the function C f,f , and

wherein the demerit factor is defined as:

d

=

1

M

s

!=

0

2

N

-

1

C

f

,

g

(

s

,

d

)

2

C

f

,

f

(

0

,

d

)

·

C

g

,

g

(

0

,

d

)

,

wherein C g,g is a one-dimensional discrete auto-correlation of a color-coded sequence g, C f,g is a one-dimensional discrete cross-correlation of the color-coded sequence f and the color-coded sequence g.

14. The computer-implemented system of claim 8 , the operations further comprise:

randomly selecting a second color-coded sequence from the set of color-coded sequences;

illuminating a second subject in accordance with the sequence of colors in the second color-coded sequence;

capturing a second sequence of images of the second subject, wherein the second sequence of images are temporally synchronized with illumination by the second color-coded sequence;

generating, by a matched filtering process using the second selected color-coded sequence, a second filtered response image from the second sequence of images of the second subject;

determining, based on the second filtered response image, that the second subject is a live person; and

responsive to determining that the second subject is the live person, initiating an authentication process for determining if the live person is authorized to access the secure system.

15. A non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising:

obtaining a set of multiple color-coded sequences, wherein each color-coded sequence comprises a sequence of colors, wherein each color-coded sequence has auto-correlation properties characterized by a merit factor larger than a first predetermined threshold, and cross-correlation properties among the color-coded sequences characterized by a demerit factor lower than a second predetermined threshold;

randomly selecting a color-coded sequence from the set of color-coded sequences;

illuminating a subject in accordance with the sequence of colors in the selected color-coded sequence;

capturing a sequence of images of the subject, wherein the sequence of images are temporally synchronized with illumination by the color-coded sequence;

generating, by a matched filtering process using the selected color-coded sequence, a filtered response image from the sequence of images of the subject;

determining, based on the filtered response image, that the subject is an alternative representation of a live person; and

responsive to determining that the subject is the alternative representation of the live person, preventing access to a secure system.

16. The non-transitory, computer-readable medium of claim 15 , wherein the alternative representation of the live person comprises a previously captured photograph of the live person printed on paper, or an image presented on a display device.

17. The non-transitory, computer-readable medium of claim 15 , wherein the alternative representation of the live person comprises video replay of the live person on a display device.

18. The non-transitory, computer-readable medium of claim 15 , wherein determining, based on the filtered response image, that the subject is the alternative representation of the live person comprises processing the filtered response image using a machine learning process trained to discriminate between filtered response images of live persons and filtered response images of alternative representations of the live persons.

19. The non-transitory, computer-readable medium of claim 15 , wherein generating, by the matched filtering process using the selected color-coded sequence, the filtered response image from the sequence of images of the subject comprises:

generating, from the sequence of images, a sequence of spatially aligned images;

calculating a sequence of filtered response images by applying a matched filter to the sequence of spatially aligned images, wherein the matched filter corresponds to the selected color-coded sequence; and

selecting the filtered response image from the sequence of filtered response images.

20. The non-transitory, computer-readable medium of claim 15 , wherein the merit factor is defined as:

d

=

1

M

C

f

,

f

(

0

,

d

)

2

s

!=

0

2

N

-

1

C

f

,

f

(

s

,

d

)

2

,

wherein M is a total number of colors in the color-coded sequence, N is length of the color-coded sequence, d is an index for the colors, C f,f is a one-dimensional discrete auto-correlation function of a color-coded sequence f, s is a correlation index in the function C f,f , and

wherein the demerit factor is defined as:

d

=

1

M

s

!=

0

2

N

-

1

C

f

,

g

(

s

,

d

)

2

C

f

,

f

(

0

,

d

)

·

C

g

,

g

(

0

,

d

)

,

wherein C g,g is a one-dimensional discrete auto-correlation of a color-coded sequence g, C f,g is a one-dimensional discrete cross-correlation of the color-coded sequence f and the color-coded sequence g.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 29, 2022
From: EYEVERIFY INC.
To: JUMIO CORPORATION
Reel/Frame 061004/0708 →
CORRECTIVE ASSIGNMENT TO CORRECT THE RECEIVING PARTY NAME PREVIOUSLY RECORDED ON REEL 057022 FRAME 0606. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded May 10, 2022
From: VEMULAPALLI, SPANDANA; HIRVONEN, DAVID
To: EYEVERIFY INC.
Reel/Frame 059924/0680 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 29, 2021
From: VEMULAPALLI, SPANDANA; HIRVONEN, DAVID
To: EYEVERIFY, INC.
Reel/Frame 057022/0606 →
Cited By (7)
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