Method of pupil segmentation

• US 8,682,073 B2
• Filed: 04/28/2011
• Issued: 03/25/2014
• Est. Priority Date: 04/28/2011
• Status: Active Grant

• Current Assignee: Iristrac LLC, Princeton Identity Inc.
• Original Assignee: SRI International, Inc.
• Inventors: Bergen, James Russell
• Primary Examiner(s): Sherali, Ishrat I
• Application Number:
  US13/096,716
• Publication Number:
  US 20120275664A1
• Time in Patent Office: 1,062 Days
• Field of Search: 382115-118, 382/173, 382/284, 382/165, 382/108, 902/3, 902/6, 340/5.53, 340/5.83, 348/78, 348/161, 713/186
• US Class Current: 382/173
• CPC Class Codes: G06V 40/18 Eye characteristics, e.g. of the iris

Abstract

A method of pupil segmentation in a digital image of a vertebrate eye, said image being an intensity image composed of pixels having each a specific intensity value, the method comprising the steps of:

• • deriving a texture image from the intensity image, said texture image being composed of pixels having each a specific contrast value;
  • forming a combined image by point-wise combining the intensity image with the texture image,
  • identifying a set of pixels in the combined image which fulfill a combined low-intensity and low-contrast criterion; and
  • approximating a boundary of said set by a convex curve and taking said convex curve as a boundary of the pupil.

Claims

1. A method of pupil segmentation in a digital image of a vertebrate eye, said image being an intensity image composed of pixels having each a specific intensity value, the method comprising the steps of:

deriving a texture image from the intensity image, said texture image being composed of pixels having each a specific contrast value;

forming a combined image by point-wise combining the intensity image with the texture image,

identifying a set of pixels in the combined image which fulfill a combined low-intensity and low-contrast criterion; and

approximating a boundary of said set by a convex curve and taking said convex curve as a boundary of the pupil.

2. The method according to claim 1, wherein said convex curve is a convex hull of said set of pixels.

3. The method according to claim 1, wherein said combined image is a product image formed by point-wise multiplication of the intensity image with the texture image, and said combined low-intensity and low-contrast criterion is a threshold criterion for the product image.

4. The method according to claim 3, wherein a threshold for said threshold criterion is determined individually for the digital image, based on a histogram analysis of the product image.

5. The method according to claim 4, wherein the histogram analysis comprises identifying a peak at a lower end of a range of product values appearing in the product image, and the threshold is selected to separate said peak from the rest of the histogram.

6. The method according to claim 5, wherein said histogram analysis comprises a filtering operation for smoothening the histogram, said filtering operation being performed before the peak is identified.

7. The method according to claim 1, comprising a check whether a dimension of said boundary of the pupil, as described by said convex curve, is within a predetermined range.

8. The method according to claim 7, comprising a step of measuring a distance between the eye and a camera with which the digital image is captured, and a step of scaling the intensity image in proportion to the distance between the camera and the eye, such that dimensions of a detail in the image of the eye indicate the corresponding true dimensions of the detail in the real eye.

9. The method according to claim 7, wherein the segmentation process is aborted and the image is rejected when the dimension of the pupil boundary is not in said predetermined range.

10. The method according to claim 7, wherein, when said dimension is not in the predetermined range, the steps of identifying a set of pixels fulfill the combined low-intensity and low-contrast criterion and of approximating the boundary of said set by a convex curve are repeated for a combined low-intensity and low-contrast criterion.

11. The method according to claim 10, wherein the segmentation process is aborted and the image is rejected when the dimension of the pupil boundary is not in the predetermined range after the combined low-intensity and low-contrast criterion has been modified a predetermined number of times.

12. The method according to claim 1, for a digital image that includes a specularity pattern caused by reflection of at least one light source at a cornea of the eye, the method comprising a step of removing said specularity pattern from the intensity image before the other steps of the segmentation are performed.

13. The method according to claim 12, wherein an inpainting algorithm is used for removing the specularity pattern.

14. The method according claim 1, wherein said convex curve is a closed geometrical line object that can only be described by more than five independent parameters.

15. The method according to claim 13, wherein said line object is a polygon approximating a smooth closed curve.

19. A non-transitory computer readable medium storing a computer program to perform the method of claim 1.

16. A method of creating a binary iris code from a digital image of a vertebrate eye, including humans, with pupil segmentation, wherein said image is an intensity image composed of pixels having each a specific intensity value, the method comprising the steps of:

deriving a texture image from the intensity image, said texture image being composed of pixels having each a specific contrast value;

forming a combined image by point-wise combining the intensity image with the texture image;

identifying a set of pixels in the combined image which fulfill a combined low-intensity and low-contrast criterion;

approximating a boundary of said set by a convex curve and taking said convex curve as a boundary of the pupil; and

transforming a digital image of the iris into a coordinate system in which each point on the iris is described by a first coordinate that indicates the position of the point along the boundary of the pupil and a second coordinate indicates the distance of the point from said boundary.

17. An iris code generation kit comprising a camera and software and hardware suitable for carrying out the method of pupil segmentation in a digital image of a vertebrate eye, said image being an intensity image composed of pixels having each a specific intensity value, the method comprising the steps of:

deriving a texture image from the intensity image, said texture image being composed of pixels having each a specific contrast value;

forming a combined image by point-wise combining the intensity image with the texture image;

identifying a set of pixels in the combined image which fulfill a combined low-intensity and low-contrast criterion; and

approximating a boundary of said set by a convex curve and taking said convex curve as a boundary of the pupil.

18. An identification system for identifying vertebrates, including humans, on the basis of an iris code match, comprising at least one iris code generation kit comprising a camera and software and hardware suitable for carrying out the method of pupil segmentation in a digital image of a vertebrate eye, said image being an intensity image composed of pixels having each a specific intensity value, the method comprising the steps of:

deriving a texture image from the intensity image, said texture image being composed of pixels having each a specific contrast value;

forming a combined image by point-wise combining the intensity image with the texture image;

identifying a set of pixels in the combined image which fulfill a combined low-intensity and low-contrast criterion; and

approximating a boundary of said set by a convex curve and taking said convex curve as a boundary of the pupil.