📄 normaliseiris.m
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% normaliseiris - performs normalisation of the iris region by
% unwraping the circular region into a rectangular block of
% constant dimensions.
%
% Usage:
% [polar_array, polar_noise] = normaliseiris(image, x_iris, y_iris, r_iris,...
% x_pupil, y_pupil, r_pupil,eyeimage_filename, radpixels, angulardiv)
%
% Arguments:
% image - the input eye image to extract iris data from
% x_iris - the x coordinate of the circle defining the iris
% boundary
% y_iris - the y coordinate of the circle defining the iris
% boundary
% r_iris - the radius of the circle defining the iris
% boundary
% x_pupil - the x coordinate of the circle defining the pupil
% boundary
% y_pupil - the y coordinate of the circle defining the pupil
% boundary
% r_pupil - the radius of the circle defining the pupil
% boundary
% eyeimage_filename - original filename of the input eye image
% radpixels - radial resolution, defines vertical dimension of
% normalised representation
% angulardiv - angular resolution, defines horizontal dimension
% of normalised representation
%
% Output:
% polar_array
% polar_noise
%
% Author:
% Libor Masek
% masekl01@csse.uwa.edu.au
% School of Computer Science & Software Engineering
% The University of Western Australia
% November 2003
function [polar_array, polar_noise] = normaliseiris(image, x_iris, y_iris, r_iris,...
x_pupil, y_pupil, r_pupil,eyeimage, radpixels, angulardiv)
global DIAGPATH
radiuspixels = radpixels + 2;
angledivisions = angulardiv-1;
r = 0:(radiuspixels-1);
theta = 0:2*pi/angledivisions:2*pi;
x_iris = double(x_iris);
y_iris = double(y_iris);
r_iris = double(r_iris);
x_pupil = double(x_pupil);
y_pupil = double(y_pupil);
r_pupil = double(r_pupil);
% calculate displacement of pupil center from the iris center
ox = x_pupil - x_iris;
oy = y_pupil - y_iris;
if ox <= 0
sgn = -1;
elseif ox > 0
sgn = 1;
end
if ox==0 && oy > 0
sgn = 1;
end
r = double(r);
theta = double(theta);
a = ones(1,angledivisions+1)* (ox^2 + oy^2);
% need to do something for ox = 0
if ox == 0
phi = pi/2;
else
phi = atan(oy/ox);
end
b = sgn.*cos(pi - phi - theta);
% calculate radius around the iris as a function of the angle
r = (sqrt(a).*b) + ( sqrt( a.*(b.^2) - (a - (r_iris^2))));
r = r - r_pupil;
rmat = ones(1,radiuspixels)'*r;
rmat = rmat.* (ones(angledivisions+1,1)*[0:1/(radiuspixels-1):1])';
rmat = rmat + r_pupil;
% exclude values at the boundary of the pupil iris border, and the iris scelra border
% as these may not correspond to areas in the iris region and will introduce noise.
%
% ie don't take the outside rings as iris data.
rmat = rmat(2:(radiuspixels-1), :);
% calculate cartesian location of each data point around the circular iris
% region
xcosmat = ones(radiuspixels-2,1)*cos(theta);
xsinmat = ones(radiuspixels-2,1)*sin(theta);
xo = rmat.*xcosmat;
yo = rmat.*xsinmat;
xo = x_pupil+xo;
yo = y_pupil-yo;
% extract intensity values into the normalised polar representation through
% interpolation
[x,y] = meshgrid(1:size(image,2),1:size(image,1));
polar_array = interp2(x,y,image,xo,yo);
% create noise array with location of NaNs in polar_array
polar_noise = zeros(size(polar_array));
coords = find(isnan(polar_array));
polar_noise(coords) = 1;
polar_array = double(polar_array)./255;
% start diagnostics, writing out eye image with rings overlayed
% get rid of outling points in order to write out the circular pattern
coords = find(xo > size(image,2));
xo(coords) = size(image,2);
coords = find(xo < 1);
xo(coords) = 1;
coords = find(yo > size(image,1));
yo(coords) = size(image,1);
coords = find(yo<1);
yo(coords) = 1;
xo = round(xo);
yo = round(yo);
xo = int32(xo);
yo = int32(yo);
ind1 = sub2ind(size(image),double(yo),double(xo));
image = uint8(image);
image(ind1) = 255;
%get pixel coords for circle around iris
[x,y] = circlecoords([x_iris,y_iris],r_iris,size(image));
ind2 = sub2ind(size(image),double(y),double(x));
%get pixel coords for circle around pupil
[xp,yp] = circlecoords([x_pupil,y_pupil],r_pupil,size(image));
ind1 = sub2ind(size(image),double(yp),double(xp));
image(ind2) = 255;
image(ind1) = 255;
%replace NaNs before performing feature encoding
coords = find(isnan(polar_array));
polar_array2 = polar_array;
polar_array2(coords) = 0.5;
avg = sum(sum(polar_array2)) / (size(polar_array,1)*size(polar_array,2));
polar_array(coords) = avg;
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