Iris image-based recognition system

• US 20060008124A1
• Filed: 07/12/2005
• Published: 01/12/2006
• Est. Priority Date: 07/12/2004
• Status: Abandoned Application

• Current Assignee: Universiti Telekom Sendirian Berhad (Telekom Malaysia Berhad)
• Original Assignee: Universiti Telekom Sendirian Berhad (Telekom Malaysia Berhad)
• Inventors: Lee, Peik Shyan, Ewe, Hong Tat
• Application Number:
  US11/178,454
• Publication Number:
  US 20060008124A1
• Time in Patent Office: Days
• US Class Current: 382/117
• CPC Class Codes: G06V 40/18 Eye characteristics, e.g. of the iris

Abstract

The present invention is to identify an individual from his or her iris captured from an imaging system. Basically the system can be divided into two processes, which are enrollment and verification. Each process consists of four steps. Both processes share the three beginning steps, which are image acquisition, image processing, and feature extraction. Image acquisition is to capture the real iris image of a user. Then image processing is applied to the acquired image. In the next step, the textural information of an iris image is generated into a signature in a process called feature extraction. For an enrollment process, the extracted iris signature will be stored in database for the future use of verification. In a verification process, the last step is to compare the iris signature generated from real time processing with the signatures previously stored. A final decision will be made to determine whether the user is successfully identified or not. The present invention introduces two new methods in the iris recognition algorithm. First, a new method called maximum vote finding method that is used during iris image processing was developed to reduce the time required for localization of inner iris after applying Hough Transform for localization of outer iris. Second, an iris signature based on fractal dimension characterization which is a novel approach used in iris feature extraction process was developed to provide satisfactory matching accuracy of iris images.

Claims

1. A method of identifying an individual by iris image-based recognition system comprising the steps of:

obtaining an iris image of said individual to be identified by locating the outer boundary and the inner boundary of an iris, whereby said inner boundary of said iris is localized using maximum vote finding method;

processing said localized iris image to extract iris features by transforming said localized image into a polar coordinate system;

extracting the characteristic values of fractal dimension from said image area for generating an identification code; and

comparing said characteristic values of said extracted identification code with the characteristic values of a previously stored identification code of said individual.

2. The method of identifying an individual by iris image-based recognition system as claimed in claim 1, wherein said obtaining the iris image comprising the further step of illuminating said iris to acquire said iris image.

3. The method of identifying an individual by iris image-based recognition system as claimed in claim 1, wherein said inner boundary which is the pupillary boundary of said iris is localized by said maximum vote finding method whereby the center coordinate of inner boundary of said iris is defined by (x_{i max}, y_{i max}) and r_{i max} is determined as radius of inner boundary.

4. The method of identifying an individual by iris image-based recognition system as claimed in claim 3, wherein said maximum vote for x-coordinate and y-coordinate of said inner boundary is defined by the following definitions:

5. The method of identifying an individual by iris image-based recognition system as claimed in claim 3, wherein said radius of inner boundary is defined by the following definition:

r_i=√

{square root over ((x_i(p)−

x_{i max})²+(y(p)−

y_{i max})²)}

vote (r_i)=vote(r_i)+1

r_i=√

{square root over ((x_r(p)−

x_{i max})²+(y(p)−

y_{i max})²)}

vote (r_i)=vote(r_i)+1

where p=−

r_o+1 to r_o−

1 for example that there are only 2 feature points detected for row p excluding the feature points of outer boundary, the above process is repeated for y-coordinate with varying column values (q) to get vote (r_i) and r_{i max}=value of vote(r_i) with maximum vote for all p and q.

6. The method of identifying an individual by iris image-based recognition system as claimed in claim 1, wherein said method further comprising the step of normalizing said transformed iris image to standardize the size.

7. The method of identifying an individual by iris image-based recognition system as claimed in claim 6, wherein said iris image is transformed into polar coordinate system by the relationship:

8. The method of identifying an individual by iris image-based recognition system as claimed in claim 1, wherein said step of extracting characteristic values is a surface coverage method to calculate fractal dimension for the image and said coverage method further comprising:

a predetermined area used as the basic measuring unit;

value of fractal dimension, D, of an object defined by log(N_r)/log [1/r] where N_r is total number of predetermined areas needed to fill up the selected surface within a portion and r equals to 1/L; and

sliding window technique that moves the current portion in u and v direction, and each time the surface bounded by the window is used to obtain the fractal dimensions of such surface.

9. The method of identifying an individual by iris image-based recognition system as claimed in claim 1, wherein said comparing said characteristic values step includes the steps of:

measuring the disagreement of two iris identification code that is one previously stored in a database and another produced from real time processing by computing an elementary modified exclusive-OR logical operator; and

comparing said two iris identification code for their Agreement Ratio (AR) which is defined as following definition;

$\mathrm{AR}=\mathrm{Total}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{number}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{of}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{comparisons}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{for}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{all}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{values}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{in}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{the}<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{signature};<br><br>$

a threshold to determined pass or fail identification where if the measured AR of comparison is lower than threshold, an imposter is rejected whereas if the measured AR is higher than threshold an enroller user is identified.