Image normalization using Daugman Rubber sheet model

Hello everyone. i have segmenated image of iris and i need to normalize it using daugman rubber sheet model. i tried using https://www.mathworks.com/matlabcentral/fileexchange/51246-pupil-limbus-detection-and-daugman-normalization but i cannot get the output.

here's the error. can expalin how to use it?

i also put declaration like this; and dont get the output

% % Input parameters

% xPosPupil = 625;

% yPosPupil = 306;

% rPupil = 70;

% xPosIris = 625;

% yPosIris = 306;

% rIris = 250;

Answer 1

[Frank Martin]

You are calling the daugmanCircleDetection function which complains that it cannot find the class ASSStack. To solve this you should make sure that Matlab can find the class (https://github.com/frankcorneliusmartin/IrisAlgorithms/blob/master/Classes/ASSStack.m) . However: The function daugmanCircleDetection is used to segment the limbus and pupil, and not for normalization.

You should call the function rubberSheetNormalisation instead to perform the normalization, which is defined in https://github.com/frankcorneliusmartin/IrisAlgorithms/blob/master/Segmentation/rubberSheetNormalisation.m

Too see how this function works see example:https://github.com/frankcorneliusmartin/IrisAlgorithms/blob/master/Examples/RubbersheetModel.m

[syahira samsudin]

ohh okay sorry, im not good in coding. thank you so much for helping me sir.

before i run rubberSheetNormalisation.m, i should change the input parameter in example then paste it in rubberSheetNormalisation.m. it that how to do it?

[Frank Martin]

That would be a valid way to do this yes.

[syahira samsudin]

this is how i insert the coding. is it correct?

function image = rubberSheetNormalisation( img, xPosPupil, yPosPupil, rPupil , xPosIris , yPosIris , rIris , varargin )

%rubberSheetNormalisation, function that normalizes the iris region. This is

%the region between the pupil boundary and the limbus. This is done

%according to the rubber sheet model proposed by Daugman (1).

%

% SYNOPSIS

% - image = rubberSheetNormalisation( img, xPosPupil, yPosPupil, rPupil , xPosIris , yPosIris , rIris )

% - image = rubberSheetNormalisation( img, xPosPupil, yPosPupil, rPupil , xPosIris , yPosIris , rIris , 'DebugMode' , 1 )

%

% INPUTS

% - img <double>

% Eye image from the cassini, preferably a NIR image. If no image

% is supplied, a pop up will ask to select one.

% - xPosPupil <integer>, yPosPupil <integer>, rPupil <integer>

% The x,y-position of the pupil center and the pupil radius

% - xPosIris <integer>, yPosIris <integer>, rIris <integer>

% The x,y-position of the iris center and the iris radius

% - varargin <optional>, input scheme

% 'DebugMode': {0: off, 1: on} - if set to 1 shows extra info

% 'AngleSamples': <integer> - number of radial samples

% 'RadiusSamples': <integer> - number of radius samples

% 'UseInterpolation': <boolean> - if 1, the samples will be

% interpolated else nearest neighbor interpolation is used.

%

% OUTPUT

% - image, containing the normalized iris region

%

% DEPENDANCIES

% - Communications Toolbox

% - Computer Vision System Toolbox (for debugmode)

%

% HISTORY

% - 26th may 2017: removed Communications Toolbox

% - 19th June 2016: added the interpolation option

%

% REFERENCES

% (1) How iris recognition works, Daugman, J.G.

%

% AUTHOR

% F.C. Martin <[e-mail]>

% 19th of May 2015 - 26th may 2017

%

% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

% Load the image

img = imread('1.jpg');

% Input parameters

xPosPupil = 1007;

yPosPupil = 947;

rPupil = 503;

xPosIris = 313;

yPosIris = 323;

rIris = 156;

% Normalize the iris region according to daugmans model

irisRegion = rubberSheetNormalisation( img, xPosPupil, yPosPupil, rPupil , xPosIris , yPosIris , rIris, 'DebugMode', 1 );

%todo: remove for-loop for line detection

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

img = rgb2gray(img);

end

% parse input

p = inputParser();

addRequired( p , 'xPosPupil' , @isnumeric );

addRequired( p , 'yPosPupil' , @isnumeric );

addRequired( p , 'rPupil' , @isnumeric );

addRequired( p , 'xPosIris' , @isnumeric );

addRequired( p , 'yPosIris' , @isnumeric );

addRequired( p , 'rIris' , @isnumeric );

addOptional( p , 'AngleSamples', 360 ,@isnumeric );

addOptional( p , 'RadiusSamples', 360 ,@isnumeric );

addOptional( p , 'DebugMode', 0, @isnumeric );

addOptional( p , 'UseInterpolation', 1, @isnumeric );

parse( p , xPosPupil, yPosPupil, rPupil , xPosIris , yPosIris , rIris , varargin{:} )

% Normalize the iris region according to daugmans model

% irisRegion = rubberSheetNormalisation( img, xPosPupil, yPosPupil, rPupil , xPosIris , yPosIris , rIris, 'DebugMode', 1 );

% Note that internally matrix coordinates are used

xp = p.Results.yPosPupil;

yp = p.Results.xPosPupil;

rp = p.Results.rPupil;

xi = p.Results.yPosIris;

yi = p.Results.xPosIris;

ri = p.Results.rIris;

angleSamples = p.Results.AngleSamples;

RadiusSamples = p.Results.RadiusSamples;

debug = p.Results.DebugMode;

interpolateQ = p.Results.UseInterpolation;

% Initialize samples

angles = (0:pi/angleSamples:pi-pi/angleSamples) + pi/(2*angleSamples);%avoiding infinite slope

r = 0:1/RadiusSamples:1;

nAngles = length(angles);

% Calculate pupil points and iris points that are on the same line

x1 = ones(size(angles))*xi;

y1 = ones(size(angles))*yi;

x2 = xi + 10*sin(angles);

y2 = yi + 10*cos(angles);

dx = x2 - x1;

dy = y2 - y1;

slope = dy./dx;

intercept = yi - xi .* slope;

xout = zeros(nAngles,2);

yout = zeros(nAngles,2);

for i = 1:nAngles

[xout(i,:),yout(i,:)] = linecirc(slope(i),intercept(i),xp,yp,rp);

end

% Get samples on limbus boundary

xRightIris = yi + ri * cos(angles);

yRightIris = xi + ri * sin(angles);

xLeftIris = yi - ri * cos(angles);

yLeftIris = xi - ri * sin(angles);

% Get samples in radius direction

xrt = (1-r)' * xout(:,1)' + r' * yRightIris;

yrt = (1-r)' * yout(:,1)' + r' * xRightIris;

xlt = (1-r)' * xout(:,2)' + r' * yLeftIris;

ylt = (1-r)' * yout(:,2)' + r' * xLeftIris;

% Create Normalized Iris Image

if interpolateQ

image = uint8(reshape(interp2(double(img),[yrt(:);ylt(:)],[xrt(:);xlt(:)]),length(r), 2*length(angles))');

else

image = reshape(img(sub2ind(size(img),round([xrt(:);xlt(:)]),round([yrt(:);ylt(:)]))),length(r), 2*length(angles));

end

% Show all points on original input image

if debug

img = insertShape(img, 'circle', [yrt(:),xrt(:),2*ones(size(xrt(:)))],'Color','r');

img = insertShape(img, 'circle', [ylt(:),xlt(:),2*ones(size(xrt(:)))],'Color','r');

figure('name','Sample scheme of the rubber sheet normalization');

imshow(img);

drawnow;

end

% Show Resulting image

figure(2);

imshow(irisRegion);

end

[Frank Martin]

I feel this is no longer in the scope of providing support for my script, as these are more general Matlab questions. I recommend you follow some basic Matlab tutorials from:

https://nl.mathworks.com/help/matlab/getting-started-with-matlab.html

[syahira samsudin]

okay thank you sir