Unable to Segment Iris from Preprocessed Eye Dataset.

The following are some images from my dataset:

I convert the coloured images in grayscale and preprocess them as follows:

function Eye= preprocessing(eyeimage)

if(size(eyeimage, 3) == 3) % if RGB image is inputted

eyeimage = rgb2gray(eyeimage);

end

%%%%%%%%% SHARPENING THE IMAGE %%%%%%%%%%%%%%%%

dimage = im2double(eyeimage);

gradient = convn(dimage,ones(3)/9,"same") - convn(dimage,ones(5)/25,"same");

amount = 5;

eyeimage = dimage + amount.*gradient;

% figure(),imshowpair(dimage,eyeimage,'montage');

% title("Original image (left) vs sharpened image (right)");

%%%%%%%%%%%%%%% Contrast-limited adaptive histogram equalization (CLAHE)%%%

% Eye = adapthisteq(eyeimage,'clipLimit',0.02,'Distribution','rayleigh');

Eye=histeq(eyeimage);

The result is:

After segemting iris from this preprocessed image:

I am not getting the correct segmented iris:

%%%%%%%%%%%%%%%%%%%%%%%% CREATEIRISTEMPLATE %%%%%%%%%%%%%%%%%%

%normalisation parameters

radial_res = 20;

angular_res = 240;

% with these settings a 9600 bit iris template is created

%feature encoding parameters

nscales=1;

minWaveLength=18;

mult=1; % not applicable if using nscales = 1

sigmaOnf=0.5;

%%%%%%%%%%%%%%%%%%%%%%%% SEGMENTIRIS %%%%%%%%%%%%%%%%%%

%CASIA

lpupilradius = 28;

upupilradius = 75;

lirisradius = 80;

uirisradius = 150;

% define scaling factor to speed up Hough transform

scaling = 0.3;

reflecthres = 240;

% find the iris boundary

[row, col, r] = findcircle(eyeimage, lirisradius, uirisradius, scaling, 2, 0.45, 0.19, 1.00, 0.00);

circleiris = [row col r];

rowd = double(row);

cold = double(col);

rd = double(r);

irl = round(rowd-rd);

iru = round(rowd+rd);

icl = round(cold-rd);

icu = round(cold+rd);

imgsize = size(eyeimage);

if irl < 1

irl = 1;

end

if icl < 1

icl = 1;

end

if iru > imgsize(1)

iru = imgsize(1);

end

if icu > imgsize(2)

icu = imgsize(2);

end

% to find the inner pupil, use just the region within the previously

% detected iris boundary

imagepupil = eyeimage( irl:iru,icl:icu);

%find pupil boundary

[rowp, colp, r] = findcircle(imagepupil, lpupilradius, upupilradius,0.2,2,0.35,0.35,1.00,1.00);

rowp = double(rowp);

colp = double(colp);

r = double(r);

row = double(irl) + rowp;

col = double(icl) + colp;

row = round(row);

col = round(col);

circlepupil = [row col r];

% set up array for recording noise regions

% noise pixels will have NaN values

imagewithnoise = double(eyeimage);

%find top eyelid

topeyelid = imagepupil(1:(rowp-r),:);

lines = findline(topeyelid);

if size(lines,1) > 0

[xl yl] = linecoords(lines, size(topeyelid));

yl = double(yl) + irl-1;

xl = double(xl) + icl-1;

yla = max(yl);

y2 = 1:yla;

ind3 = sub2ind(size(eyeimage),yl,xl);

imagewithnoise(ind3) = NaN;

imagewithnoise(y2, xl) = NaN;

end

%find bottom eyelid

bottomeyelid = imagepupil((rowp+r):size(imagepupil,1),:);

lines = findline(bottomeyelid);

if size(lines,1) > 0

[xl yl] = linecoords(lines, size(bottomeyelid));

yl = double(yl)+ irl+rowp+r-2;

xl = double(xl) + icl-1;

yla = min(yl);

y2 = yla:size(eyeimage,1);

ind4 = sub2ind(size(eyeimage),yl,xl);

imagewithnoise(y2, xl) = NaN;

end

imagewithnoise(ind4) = NaN;

%For CASIA, eliminate eyelashes by thresholding

ref = eyeimage < 100;

coords = find(ref==1);

imagewithnoise(coords) = NaN;

% figure,imshow(eyeimage);title('originalimage');

% figure,imshow(imagepupil);title('pupil');

% figure,imshow(imagewithnoise);title('image with noise');

% WRITE NOISE IMAGE

%

imagewithnoise2 = uint8(imagewithnoise);

imagewithcircles = uint8(eyeimage);

%get pixel coords for circle around iris

[xii,yii] = circlecoords([circleiris(2),circleiris(1)],circleiris(3),size(eyeimage));

ind2 = sub2ind(size(eyeimage),double(yii),double(xii));

%get pixel coords for circle around pupil

[xpp,ypp] = circlecoords([circlepupil(2),circlepupil(1)],circlepupil(3),size(eyeimage));

ind1 = sub2ind(size(eyeimage),double(ypp),double(xpp));

% Write noise regions

imagewithnoise2(ind2) = 255;

imagewithnoise2(ind1) = 255;

% Write circles overlayed

imagewithcircles(ind2) = 255;

imagewithcircles(ind1) = 255;

% figure('name',"Hough Transform locating Iris and Pupil");

% subplot(1,3,3);imshow(eyeimage);title('Original image');

% subplot(1,3,1);imshow(imagewithnoise2);title('Segmented');

% subplot(1,3,2);imshow(imagewithcircles);title('Circles');

%%%%%%%%%%%%%%%%%% MODEL2OUTPUT %%%%%%%%%%%%%%%%%

x=xii;

y=yii;

r1=ind2;

xp=xpp;

yp=ypp;

r2=ind1;

[nx,ny,d] = size(I) ;

[X,Y] = meshgrid(1:ny,1:nx) ;

th = linspace(0,2.*pi);

x=double(x);

y=double(y);

r1=double(r1);

xp=double(xp);

yp=double(yp);

r2=double(r2);

idx = inpolygon(X(:),Y(:),x,y) ;

for i = 1:d

I1 = I(:,:,i) ;

I1(~idx) = 255 ;

I(:,:,i) = I1 ;

end

idx = inpolygon(X(:),Y(:),xp,yp) ;

for i = 1:d

I1 = I(:,:,i) ;

I1(idx) = 255 ;

I(:,:,i) = I1 ;

end

figure('name',"Segmented Iris"),imshow(I);

I think the problem is in the findcircle parameters. Can anyone help me with the parameters I must put in findcircle function?

Attaching the findcircle file for the reference.

Answer 1

[Taylor]

Have you considered just using imfindcircles?

[Ridhima Chopra]

i don't get you actually.

I tried changing the parameters like scaling, high threshold and lower threshold for these lines:

%find iris boundary

[row, col, r] = findcircle(eyeimage, lirisradius, uirisradius, scaling, 2, 0.45, 0.19, 1.00, 0.00);

%find pupil boundary

[rowp, colp, r] = findcircle(imagepupil, lpupilradius, upupilradius,0.2,2,0.35,0.35,1.00,1.00);

After making changes, it works perfectly for some images but doesn't for the others.

[Ridhima Chopra]

Okay now i get it, imfindcircles doesn't work on this one. It works only where backgrounds are brighter than the objects. @Taylor

[Taylor]

@Ridhima Chopra Set the ObjectPolarity to "bright" when the circular objects are brighter than the background and "dark" when the circular objects are darker than the background.

[Ridhima Chopra]

Ok will try. Thanks.

[Image Analyst]

imfindcircles is a built-in function. Try that instead of this home-built findcircles function you're using.

[Ridhima Chopra]

It detected a number of circles

[Ridhima Chopra]

Not as accurate as findcircles function.

[Taylor]

There are various ways to fine tune imfindcircles. Namely, using a radius range and adjusting the values for sensitivity and edge threshold.

[Ridhima Chopra]

It works thanks @Taylor @Image Analyst