color code of the curvatureCurve Fitting ToolboxImage Processing Toolbox
% Routine to find the optic disc in one particular image.
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format long g;format compact;fontSize = 20;%===============================================================================
% Read in gray scale demo image.
folder = pwd; % Determine where demo folder is (works with all versions).
baseFileName = 'i.jpg';% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);% Check if file exists.
if ~exist(fullFileName, 'file') % The file doesn't exist -- didn't find it there in that folder.
% Check the entire search path (other folders) for the file by stripping off the folder.
fullFileNameOnSearchPath = baseFileName; % No path this time.
if ~exist(fullFileNameOnSearchPath, 'file') % Still didn't find it. Alert user.
errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName); uiwait(warndlg(errorMessage)); return; endendrgbImage = imread(fullFileName);% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(rgbImage)if numberOfColorChannels > 1 % It's not really gray scale like we expected - it's color.
% Use weighted sum of ALL channels to create a gray scale image.
% grayImage = rgb2gray(rgbImage);
% ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
% which in a typical snapshot will be the least noisy channel.
grayImage = rgbImage(:, :, 2); % Take green channel.
else grayImage = rgbImage; % It's already gray scale.
end% Now it's gray scale with range of 0 to 255.
% Display the image.
subplot(2, 2, 1);imshow(grayImage, []);title('Original Image', 'FontSize', fontSize, 'Interpreter', 'None');axis('on', 'image');hp = impixelinfo();%------------------------------------------------------------------------------
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0.04, 1, 0.96]);% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')drawnow;% Optic disk is known to be on the left, so erase the image on the right.
clippedImage = grayImage; % Initialize.
clippedImage(:, 1200:end) = grayImage(1,1); % Set equal to surrounding template.
% Show the histogram
subplot(2, 2, 2);[counts, grayLevels] = histcounts(clippedImage(:));counts(counts == max(counts)) = 0; % Suppress spike
bar(grayLevels(1:end-1), counts);grid on;title('Histogram of Original Image', 'FontSize', fontSize, 'Interpreter', 'None');% Binarize the image
binaryImage = clippedImage >= 245;% Take largest blob
binaryImage = bwareafilt(binaryImage, 1);% Take convex hull
binaryImage = bwconvhull(binaryImage);% Display the image.subplot(2, 2, 3);imshow(binaryImage, []);title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');axis('on', 'image');hp = impixelinfo();% It is known/assumed that the optic disk's "good part" is on the right,
% so find pixels on the right side.
% First find boundaries
boundaries = bwboundaries(binaryImage);xBoundary = boundaries{1}(:, 2);yBoundary = boundaries{1}(:, 1);% Scan down finding right edge
xRight = zeros(1, columns);yRight = zeros(1, columns);for row = 1 : rows x = find(binaryImage(row, :), 1, 'last'); if ~isempty(x) xRight(row) = x; yRight(row) = row; endend% Get rid of rows with no object in them.
noObjectRows = xRight == 0;xRight(noObjectRows) = [];yRight(noObjectRows) = [];% Fit xRight and yRight to a circle
[xCenter, yCenter, R, a] = circfit(xRight,yRight);% Plot over image.
% Display the image.subplot(2, 2, 4);imshow(grayImage, []);title('Original Image with Disc Circled', 'FontSize', fontSize, 'Interpreter', 'None');axis('on', 'image');hp = impixelinfo();viscircles([xCenter, yCenter], R);% Circle fitting routine from the FAQ.
function [xc,yc,R,a] = circfit(x,y)%CIRCFIT Fits a circle in x,y plane
%
% [XC, YC, R, A] = CIRCFIT(X,Y)
% Result is center point (yc,xc) and radius R. A is an optional
% output describing the circle's equation:
%% x^2+y^2+a(1)*x+a(2)*y+a(3)=0
% by Bucher izhak 25/oct/1991
n=length(x); xx=x.*x; yy=y.*y; xy=x.*y;A=[sum(x) sum(y) n;sum(xy) sum(yy) sum(y);sum(xx) sum(xy) sum(x)];B=[-sum(xx+yy) ; -sum(xx.*y+yy.*y) ; -sum(xx.*x+xy.*y)];a=A\B;xc = -.5*a(1);yc = -.5*a(2);R = sqrt((a(1)^2+a(2)^2)/4-a(3));end
boundaries=bwboundaries(handImage1); % get;s the boudaries of the feature present in the image, the output is cell
x = boundaries{1}(:, 2); % select x coordinates of first boundary
y = boundaries{1}(:, 1); % select y coordinates of first boundary
hold on;plot(x, y, 'black', 'LineWidth', 2); % plotting the first boundary
newImage = bwlabel(handImage1); % labelling the image
measurements = regionprops(newImage, 'Centroid', 'BoundingBox'); % get the properits of the region
% picking the centroid of the first label
xCentroid = measurements.Centroid(1);yCentroid = measurements.Centroid(2);subplot(2, 2, 4); % sub plotting
imshow(newImage); % shows image
title('Binary Image with Centroid Marked'); hold on;plot(xCentroid, yCentroid, 'r*', 'MarkerSize', 10, 'LineWidth', 2); % plotting the coentorid
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