Iris recognition system having image quality metrics

• US 8,050,463 B2
• Filed: 03/02/2007
• Issued: 11/01/2011
• Est. Priority Date: 01/26/2005
• Status: Active Grant

• Current Assignee: Gentex Corporation
• Original Assignee: Honeywell International Inc.
• Inventors: Hamza, Rida M.
• Primary Examiner(s): Le, Brian Q
• Application Number:
  US11/681,614
• Publication Number:
  US 20070274570A1
• Time in Patent Office: 1,705 Days
• Field of Search: 382/103, 382/115, 382/117, 382/118, 382/154, 356/4.03, 356/4.04, 356/4.05, 356/4.06, 356/4.07, 356/18, 356/492, 356/493, 356/496, 356/498
• US Class Current: 382/115
• CPC Class Codes: G06V 10/993 Evaluation of the quality of the acquired pattern
• CPC Class Codes: G06V 40/193 Preprocessing; Feature extraction

Abstract

An iris recognition system implementing image quality metrics to assess the quality of an acquired eye image for reliable operation. Images with low image quality may be rejected or flagged based upon the application. The image quality may be determined with a preprocessing module in the recognition system. The processing may be configured based on a quality assessment.

Claims

1. A computer implemented iris image quality metric system comprising:

a device for acquiring an iris image; and

a data-processing apparatus;

a quality processing module connected to the device;

wherein the quality processing module is executed by the data-processing apparatus, the module and data-processing apparatus are operated in combination to provide a quality assessment of an iris image;

wherein the quality assessment of the iris image includes an assessment of image blur; and

image blur is measured according to high frequency distortions from coarse to fine wavelet coefficients.

2. The system of claim 1, wherein the quality assessment of an iris image further includes an analysis of one or more of the following image conditions which comprise:

defocus;

closure;

obscuration;

off-angle detection;

reflection; and

/or

excessive dilation.

3. The system of claim 1, wherein a quality assessment of the iris image includes an analysis of the iris image relative to iris obscuration including a computation of an integral of virtually total area between an eyelid curve and an iris inner boundary of an eye from which the iris image is taken.

4. The system of claim 1, wherein a quality assessment of the iris image includes an analysis based on an XOR-ing of codes of two patches of the iris image to measure a discrepancy among bits of the patches.

5. The system of claim 1, wherein a quality assessment of the iris image includes an analysis based on measuring similarity of two patches of the iris image using contrast similarity, intensity distribution similarity, peak signal to noise ratio, and/or correlation between intensities of the two patches.

6. The system of claim 1, wherein a quality assessment of the iris image includes an analysis of the iris image relative to an amount of reflection by the iris in the image including an iris curve fitting and a contrast thresholding.

10. The system of claim 1, wherein a quality assessment of the iris image includes an analysis of the iris image relative to eye closure including an analysis of an inner border profile of the iris in the image.

11. The system of claim 10, wherein the inner border profile is estimated according to a measurement of an amount that a detected curve of the profile is similar to an elliptic-like shape, and a measurement of an amount of exposure of a map of the iris.

7. A computer implemented iris image quality metric system comprising:

a device for acquiring an iris image;

a data-processing apparatus; and

a quality processing module connected to the device;

wherein the quality processing module is executed by the data-processing apparatus, the module and data-processing apparatus are operated in combination to provide a quality assessment of an iris image;

wherein a quality measurement relative to blur and/or defocus of the iris image is based on a measurement of energy at high frequencies of the spectral domain of the image;

wherein the measurement of energy at high frequencies of the spectral domain of the image is compared to a measurement of energy at high frequencies of the spectral domain of the image without blur and/or defocus; and

an amount that the energy at high frequencies of the spectral domain of the image is less than the energy at high frequencies of the spectral domain of the image without blur and/or defocus is proportional to the blur and/or defocus of the image.

8. A computer implemented iris image quality metric system comprising:

a device for acquiring an iris image;

a data-processing apparatus; and

a quality processing module connected to the device;

wherein the quality processing module is executed by the data-processing apparatus, the module and data-processing apparatus are operated in combination to provide a quality assessment of an iris image;

wherein the quality assessment of the iris image is according to blur;

blur is measured according to high frequency distortions from coarse to fine wavelet coefficients; and

wherein the high frequency distortions among the coarse to fine wavelet coefficients are indicated by a comparison of linear frequency distortion filter outputs at multiple stages of a dyadic decomposition to measure a discrepancy among the stages.

9. A computer implemented iris image quality metric system comprising:

a device for acquiring an iris image;

a data-processing apparatus; and

a quality processing module connected to the device;

wherein the quality processing module is executed by the data-processing apparatus, the module and data-processing apparatus are operated in combination to provide a quality assessment of an iris image;

wherein the quality assessment of the iris image is according to blur;

blur is measured according to high frequency distortions from coarse to fine wavelet coefficients; and

wherein high frequency content is compared at wavelet decompositions between two patches of the iris image for similarity purposes.

12. A computer implemented iris image quality metric system comprising:

a device for acquiring an iris image;

a data-processing apparatus; and

a quality processing module connected to the device;

wherein the quality processing module is executed by the data-processing apparatus, the module and data-processing apparatus are operated in combination to provide a quality assessment of an iris image; and

wherein a quality assessment of the iris image is according to a comparison of a location of edges of the pupil with a set of defined limits for normal operation of a pupil dilation.

13. A computer implemented iris image preprocessing system comprising:

a device for acquiring an iris image;

a data-processing apparatus;

an iris image module executed by the data-processing apparatus;

an iris image quality measurement module executed by the data-processing apparatus and connected to the iris image module;

an evaluator connected to the iris image module;

a rehabilitator connected to the evaluator;

wherein;

the evaluator receives a quality measurement of an iris image from the quality measurement module, indicates whether the iris image is acceptable or unacceptable for further processing, and indicates whether an iris image that is unacceptable should be rejected or be rehabilitated for further processing; and

the rehabilitator conditions the image by one or more of pixel processing, contrast balancing, histogram equalization, image blind deblurring, adaptive filtering for iris texture restoration, and pose normalization.

14. The system of claim 13, further comprising an image segmentation module connected to the iris image module, the image segmentation module performing one dimensional polar segmentation on the iris image.

15. A computer implemented method for assessing quality of an image comprising:

receiving an iris image from an iris image acquiring device;

measuring at least one quality of the iris image using a data-processing apparatus including a quality processing module;

evaluating the at least one quality to determine whether the iris image is adequate relative to the at least one quality for further processing;

determining whether an iris image, which is not adequate relative to the at least one quality for further processing, is adequate for rehabilitation;

if the iris image is adequate for rehabilitation, conditioning the image by one or more of pixel processing, contrast balancing, histogram equalization, image blind deblurring, adaptive filtering for iris texture restoration, and pose normalization.

16. A computer implemented method for assessing quality of an image comprising:

receiving an iris image from an iris image acquiring device;

measuring at least one quality of the iris image using a data-processing apparatus including a quality processing module;

evaluating the at least one quality to determine whether the iris image is adequate relative to the at least one quality for further processing;

measuring a first energy, at high frequencies, of the spectral domain of the iris image;

determining a second energy, at high frequencies, of the spectral domain of a model iris image which is adequate for further processing; and

wherein if the first energy is within a set percentage of the second energy, then the iris image is adequate, relative to the at least one quality, for further processing.

17. A computer implemented method for assessing quality of an image comprising:

receiving an iris image from an iris image acquiring device;

measuring at least one quality of the iris image using a data-processing apparatus including a quality processing module;

evaluating the at least one quality to determine whether the iris image is adequate relative to the at least one quality for further processing;

obtaining two different localized patches from an iris code of the iris image;

XOR-ing the two patches;

measuring an amount of discrepancy among cross-matched bits of the two patches;

determining whether the amount of discrepancy is greater than a set amount; and

wherein if the amount of discrepancy is greater than a set amount, then the iris image is adequate, relative to the at least one quality, for further processing.

18. A computer implemented method for assessing quality of an image comprising:

receiving an iris image from an iris image acquiring device;

measuring at least one quality of the iris image using a data-processing apparatus including a quality processing module;

evaluating the at least one quality to determine whether the iris image is adequate relative to the at least one quality for further processing;

measuring an amount of difference between the inner border profile in the iris image and an elliptic-like shape; and

measuring a percentage of the iris map of the iris image that is exposed; and

wherein;

if the amount of difference is less than a set difference for an iris image adequate for further processing relative to the at least one quality,

then the image is adequate for further processing relative to the at least one quality; and

if the percentage is greater than a set percentage for an iris image adequate for further processing relative to the at least one quality, then the image is adequate for further processing relative to the at least one quality.