Iris liveness detection for mobile devices
An approach for an iris liveness detection is provided. A plurality of image pairs is acquired using one or more image sensors of a mobile device. A particular image pair is selected from the plurality of image pairs, and a hyperspectral image is generated for the particular image pair. Based on, at least in part, the hyperspectral image, a particular feature vector for the eye-iris region depicted in the particular image pair is generated, and one or more trained model feature vectors generated for facial features of a particular user of the device are retrieved. Based on, at least in part, the particular feature vector and the one or more trained model feature vectors, a distance metric is determined and compared with a threshold. If the distance metric exceeds the threshold, then a first message indicating that the plurality of image pairs fails to depict the particular user is generated. It is also determined whether at least one characteristic, of one or more characteristics determined for NIR images, changes from image-to-image by at least a second threshold. If so, then a second message is generated to indicate that the plurality of image pairs depicts the particular user of a mobile device. The second message may also indicate that an authentication of an owner to the mobile device was successful. Otherwise, a third message is generated to indicate that a presentation attack on the mobile device is in progress.
1. An electronic device comprising:
a first image sensor;
a second image sensor;
one or more processors; and
one or more computer-readable media storing instructions that, when executed by the one or more processors, cause the electronic device to perform operations comprising:
generating, at a first time and using the first image sensor, first image data representing an eye;
determining, based at least in part on the first image data, a first characteristic associated with the eye;
generating, at a second time and using the first image sensor, second image data representing the eye;
determining, based at least in part on the second image data, a second characteristic associated with the eye;
determining that the eye is associated with a user based at least in part on the first characteristic and the second characteristic; and
generating, using the second image sensor, third image data representing the eye.
2. The electronic device as recited in claim 1 , the operations further comprising identifying the user based at least in part on the third image data.
3. The electronic device as recited in claim 1 , wherein:
the first image sensor is a first type of image sensor; and
the second image sensor is a second type of image sensor that is different than the first type of image sensor.
4. The electronic device as recited in claim 1 , wherein:
the first image data represents a first near infra-red image depicting the eye;
the second image data represents a second near infra-red image depicting the eye; and
the third image data represents a red-green-blue image depicting the eye.
5. The electronic device as recited in claim 1 , the operations further comprising:
determining a change between the first characteristic and the second characteristic,
and wherein determining that the eye is associated with the user is based at least in part on the change.
6. The electronic device as recited in claim 1 , the operations further comprising:
determining a change between the first characteristic and the second characteristic; and
determining that the change is equal to or greater than a threshold change,
and wherein determining that the eye is associated with the user is based at least in part on the change being equal to or greater than the threshold change.
7. The electronic device as recited in claim 1 , the operations further comprising:
determining, based at least in part on the first image data, a third characteristic associated with the eye; and
determining, based at least in part on the second image data, a fourth characteristic associated with the eye,
and wherein determining that the eye is associated with the user is further based at least in part on the third characteristic and the fourth characteristic.
8. The electronic device as recited in claim 1 , wherein:
the first characteristic includes a first size of a pupil area of the eye; and
the second characteristic includes a second size of the pupil area of the eye.
9. The electronic device as recited in claim 1 , the operations further comprising:
generating, at a third time and using the first image sensor, fourth image data representing an additional eye;
determining, based at least in part on the fourth image data, a third characteristic associated with the additional eye;
generating, at a fourth time and using the first image sensor, fifth image data representing the additional eye;
determining, based at least in part on the fifth image data, a fourth characteristic associated with the additional eye; and
identifying a spoofing attack based at least in part on the fourth image data and the fifth image data.
10. A method comprising:
generating, at a first time and using a first image sensor, first image data representing an eye;
generating, at a second time and using the first image sensor, second image data representing the eye;
determining that the eye is associated with a user based at least in part on the first image data and the second image data;
generating, using a second image sensor, third image data representing the eye; and
identifying the user based at least in part on the third image data.
11. The method as recited in claim 10 , wherein:
the first image sensor is a first type of image sensor; and
the second image sensor is a second type of image sensor that is different than the first type of image sensor.
12. The method as recited in claim 10 , wherein:
the first image data represents a first near infra-red image depicting the eye;
the second image data represents a second near infra-red image depicting the eye; and
the third image data represents a red-green-blue image depicting the eye.
13. The method as recited in claim 10 , further comprising:
determining, based at least in part on the first image data, a first characteristic associated with the eye; and
determining, based at least in part on the second image data, a second characteristic associated with the eye,
and wherein determining that the eye is associated with the user is based at least in part on the first characteristic and the second characteristic.
14. The method as recited in claim 13 , further comprising:
determining a change between the first characteristic and the second characteristic,
wherein determining that the eye is associated with the user is based at least in part on the change.
15. The method as recited in claim 13 , further comprising:
determining a change between the first characteristic and the second characteristic; and
determining that the change is equal to or greater than a threshold change,
wherein determining that the eye is associated with the user is based at least in part on the change being equal to or greater than the threshold change.
16. The method as recited in claim 13 , wherein:
the first characteristic includes a first size of a pupil area of the eye; and
the second characteristic includes a second size of the pupil area of the eye.
17. The method as recited in claim 10 , further comprising:
generating, at a third time and using the first image sensor, fourth image data representing an additional eye;
generating, at a fourth time and using the first image sensor, fifth image data representing the additional eye; and
identifying a spoofing attack based at least in part on the fourth image data and the fifth image data.
18. An electronic device comprising:
a first image sensor;
a second image sensor;
one or more processors; and
one or more computer-readable media storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
generating, at a first time and using the first image sensor, first image data representing an eye;
determining, based at least in part on the first image data, a first characteristic associated with the eye;
generating, at a second time and using the first image sensor, second image data representing the eye;
determining, based at least in part on the second image data, a second characteristic associated with the eye; and
determining that the eye is not associated with a user based at least in part on the first characteristic and the second characteristic.
19. The electronic device as recited in claim 18 , wherein:
the first image sensor is a first type of image sensor; and
the second image sensor is a second type of image sensor that is different than the first type of image sensor.
20. The electronic device as recited in claim 18 , the operations further comprising:
determining a change between the first characteristic and the second characteristic; and
determining that the change is less than a threshold change,
wherein determining that the eye is not associated with the user is based at least in part on the change being less than the threshold change.