www.pudn.com > iriscode.zip > normaliseiris.m

% 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_filename, 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; 
 
 
% write out rings overlaying original iris image 
w = cd; 
cd(DIAGPATH); 
 
imwrite(image,[eyeimage_filename,'-normal.jpg'],'jpg'); 
 
cd(w); 
 
% end diagnostics 
 
%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;