System and method for identifying a person with reference to a sclera image

1. A method for obtaining an identification characteristic for a subject comprising:

acquiring an image of an eye of a subject with a digital camera;

segmenting the eye image into different regions with a digital image processor;

extracting features in a sclera region segmented from the eye image with the digital image processor, the extraction comprising:

generating with the digital image processor a linear representation of at least one vein in the sclera region segmented from the eye image, the linear representation including a plurality of line segments that correspond to the at least one vein;

generating data identifying at least one feature extracted from the sclera region of the eye image with the digital image processor, the generation comprising:

identifying with the digital image processor data corresponding to a center and angle of each line segment in the plurality of line segments with reference to a center of a pupil in the eye image; and

storing the data identifying the at least one feature in a database with the digital image processor.

2. The method of claim 1 , the eye image segmentation further comprising:

segmenting the eye image into an iris region and sclera region with the digital image processor; and

identifying a limbic boundary between the iris region and the sclera region with the digital image processor.

3. The method of claim 2 further comprising:

identifying a medial point position and a lateral point position in the eye image with the digital image processor.

4. The method of claim 1 wherein the extracted feature is a blood vessel pattern in the sclera region.

5. The method of claim 1 further comprising:

generating with the digital image processor a model of eyelids in the eye image with a two dimensional polynomial curve.

6. The method of claim 1 , the data generation further comprising:

identifying with the digital image processor locations for vein patterns, vein lines, and extrema points in the sclera region.

7. The method of claim 1 , the data generation further comprising:

generating with the digital image processor model parameters from features via wavelet, curve fitting method, neural network, filtering method, and other pattern recognition methods.

8. The method of claim 1 further comprising:

comparing with the digital image processor identifying data generated from a first eye image to identifying data obtained from a second eye image to generate a comparison score; and

determining with the digital image processor that a subject from which the first eye image is obtained corresponds to the a subject from which the second eye image is obtained in response to the comparison score being equal to or greater than a matching threshold.

9. The method of claim 2 further comprising:

extracting features in the iris region with the digital image processor;

generating with the digital image processor data identifying at least one feature extracted from the iris region.

10. The method of claim 9 further comprising:

comparing identifying data generated for a feature extracted from the sclera region in a first eye image to identifying data generated for a feature extracted from the sclera region in a second eye image to generate a sclera comparison score with the digital image processor;

comparing identifying data generated for a feature extracted from the iris region in the first eye image to identifying data generated for a feature extracted from the iris region in the second eye image to generate an iris comparison score with the digital image processor; and

determining with the digital image processor that a subject from which the first eye image is obtained corresponds to a subject from which the second eye image is obtained in response to at least one of the sclera comparison score and the iris comparison score being equal to or greater than a matching threshold.

11. The method of claim 1 , the eye image acquisition further comprising:

illuminating the eye with a light source configured to emit one of a near infrared, infrared, visible, multispectral, and a hyperspectral frequency light.

12. The method of claim 1 , the eye image acquisition further comprising:

illuminating the eye with a light source configured to emit one of a polarized or non-polarized light.

13. The method of claim 1 , the eye image acquisition further comprising:

illuminating the eye with a light source that is close to or remote from the eye.

14. The method of claim 1 wherein the feature extraction is preceded by a feature enhancement method including:

generating a plurality of filtered images from at least one of the segmented regions by applying a plurality of image filters with the digital image processor; and

combining the filtered images into a single enhanced image of the at least one of the segmented regions with the digital image processor.

15. The method of claim 1 , the generation of identifying data further comprising:

generating with the digital image processor a bit map of the sclera region that identifies features.

16. The method of claim 1 , the generation of identifying data further comprising:

generating with the digital image processor a list of features with positional information about each feature.

17. The method of claim 1 , the generation of identifying data further comprising:

generating with the digital image processor a template for the extracted features.

18. The method of claim 1 wherein the digital image processor generates identifying data in one of a binary, integer, or floating number format.

19. The method of claim 10 wherein the subject determination includes iris and sclera feature fusion.

20. The method of claim 10 wherein the subject determination includes iris and sclera template fusion.

21. The method of claim 10 wherein the subject determination includes iris and sclera comparison score fusion.

22. A system for obtaining an identification characteristic for a subject comprising:

a digital camera configured to acquire an image of an eye of a subject;

a digital image processor configured to:

segment the eye image into different regions;

extract features in a sclera region segmented from the eye image the extraction comprising:

generation of a linear representation of at least one vein in the sclera region segmented from the eye image, the linear representation including a plurality of line segments that correspond to the at least one vein; and

generate data identifying at least one feature extracted from the sclera region of the eye image, the generation comprising:

identification of data corresponding to a center and angle of each line segment in the plurality of line segments with reference to a center of a pupil in the eye image; and

a database for storage of identifying data.

23. The system of claim 22 , the digital image processor being further configured to compare identifying data stored in the database to identifying data obtained from a second eye image to generate a comparison score; and

determining a subject from which the stored identifying data is obtained corresponds to a subject from which the second eye image is obtained in response to the comparison score being equal to or greater than a matching threshold.

24. The system of claim 22 wherein the digital camera is one of a near infrared, infrared, visible, multispectral, and hyperspectral camera.

25. The system of claim 22 wherein the digital camera is one of a polarized and non-polarized camera.

26. The system of claim 22 wherein the digital camera is located closely or remotely from the eye being imaged.