www.pudn.com > eyedemo.rar > normaliseiris.m

% normaliseiris - 通过将旋转的环形区域转换为有限维的矩形区域实现归一化 
% 
% 使用:  
% [polar_array, polar_noise] = normaliseiris(image, x_iris, y_iris, r_iris,... 
% x_pupil, y_pupil, r_pupil,eyeimage_filename, radpixels, angulardiv) 
% 
% 参数: 
% image                 - 用来处理的输入图像 
% x_iris                - 虹膜边界曲线圆心的横坐标 
% y_iris                - 虹膜边界曲线圆心的纵坐标 
% r_iris                - 虹膜边界曲线的半径 
% x_pupil               - 瞳孔边界曲线圆心的横坐标 
% y_pupil               - 瞳孔边界曲线圆心的横坐标 
% r_pupil               - 瞳孔边界曲线半径 
% eyeimage_filename     - 输入眼部图像的原始图像 
% radpixels             - 延半径方向的辐射分量, 定义归一化后图像的竖直分量 
% angulardiv            - 延角度方向的旋转分量, 定义归一化后图像的水平分量 
% 输出: 
% polar_array 
% polar_noise 
 
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); 
 
% 计算瞳孔圆心与虹膜圆心间距 
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); 
 
% 为防止ox＝0做一些事情 
if ox == 0 
    phi = pi/2; 
else 
    phi = atan(oy/ox); 
end 
 
b = sgn.*cos(pi - phi - theta); 
 
%将半径以角度的函数计算 
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; 
 
 
%排除瞳孔与虹膜，虹膜与巩膜边界处的值 
% 因为它们可能不与虹膜区域的值相应并将引入噪声 
% 即不讲边界外的圆环当作虹膜数据 
rmat  = rmat(2:(radiuspixels-1), :); 
 
% 计算环形虹膜区域中的点在笛卡儿坐标下的位置 
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; 
 
% 通过插值将像素值转入对应的归一化之后的图像像素中 
[x,y] = meshgrid(1:size(image,2),1:size(image,1));   
polar_array = interp2(x,y,image,xo,yo); 
 
% 创建噪声矩阵，它带有在极座标polar_array中的NaN的定位 
polar_noise = zeros(size(polar_array)); 
coords = find(isnan(polar_array)); 
polar_noise(coords) = 1; 
 
polar_array = double(polar_array)./255; 
 
 
% 开始诊断，输出覆盖有圆环的眼部图像 
 
% 除去虹膜之外的点来写入环形模板 
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; 
%得到外圆边界像素坐标 
[x,y] = circlecoords([x_iris,y_iris],r_iris,size(image)); 
ind2 = sub2ind(size(image),double(y),double(x)); 
%得到内圆边界像素坐标 
[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; 
 
% 在原图上写入圆环 
w = cd; 
cd('E:\MATLAB7\work\diagnostics'); 
 
%imwrite(image,[eyeimage_filename,'-normal.jpg'],'jpg'); 
 
cd(w); 
 
%结束诊断 
 
%执行特征编码前替换NaN噪声 
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;