Method for extracting features of irises in images using difference of sum filters

• US 20070160266A1
• Filed: 01/11/2006
• Published: 07/12/2007
• Est. Priority Date: 01/11/2006
• Status: Abandoned Application

• Current Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Original Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Inventors: Jones, Michael, Guo, Guodong
• Application Number:
  US11/329,624
• Publication Number:
  US 20070160266A1
• Time in Patent Office: Days
• US Class Current: 382/117
• CPC Class Codes: G06V 40/193 Preprocessing; Feature extraction

Abstract

A method for extracting features of an iris in an image is described. An unwrapped iris image is converted to an integral image by summations of pixel intensities. A novel bank of difference of sum filters is used to filter the integral image. The filtered output is binarized to produce an iris feature vector. The iris feature vector is used for iris matching.

Claims

1. A method for extracting features of an iris in an image, comprising:

detecting boundaries of an iris in an image;

mapping pixels representing the iris in the image to a rectangular image, according to the boundaries;

filtering the pixels in the rectangular image to produce filtered output, in which the filtering uses difference of sum filters;

binarizing the filtered output to produce a feature vector representing the iris.

2. The method of claim 1, in which the binarizing is according to:

$y=\mathrm{sgn}<br><br>\left(x\right)=\{\begin{array}{cc}1,& \mathrm{if}<br><br>\text{\hspace{1em}<br><br>}<br><br>x><br><br>0\\ 0,& \mathrm{otherwise}\end{array}$

where y is an entry in a feature vector, sgn( ) is a sign operator, and x is the filtered output.

3. The method of claim 1, further comprising:

producing a first feature vector for a first image of a known iris;

producing a second feature vector for a second image of an unknown iris;

measuring a Hamming distance between the first feature vector and the second feature to determine a similarity between the known iris and the unknown iris.

4. The method of claim 1, further comprising:

converting the rectangular image to an integral image according to

$\mathrm{ii}<br><br>\left(x,y\right)=\underset{x^{\mathrm{\prime <br><br>}}\le <br><br>x,y^{\mathrm{\prime <br><br>}}\le <br><br>y}{\sum <br><br>}<br><br>i<br><br>\left(x^{\mathrm{\prime <br><br>}},y^{\mathrm{\prime <br><br>}}\right)$

where ii(x, y) is an integrated pixel intensity value in the integral image and i(x, y) is a pixel intensity value in the rectangular image; and

determining the filtered output using the integral image.