Identifying blobs and area filtering

Question

Jason 2023-1-22

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1898565-identifying-blobs-and-area-filtering

评论： Jason 2023-1-25

Hello, Im trying to identify the centres of the drops in the image below. Although in each drop there is a bright area, I dont care about this.

My analysis fails when the drop in the middle picture (binary) touches the large white circle (at the green line).

1: How can I get that last drop included thats touching the boundary

Here is my code.

            IM=getimage(app.UIAxes); 
            pos=myfigure(app,1450,520);  %my own function 
            figA=figure('position',pos);
            m = uimenu(figA,Label="My Save As");
            m.MenuSelectedFcn = @app.mysavefunc;
            ax1=subplot(1,3,1);
            myImagesc(app,ax1,IM);      %My version of ImageSc
            title(ax1,'Raw Image');
            %Use adaptive thresholding as varying background
            BW = imbinarize(IM,'adaptive','ForegroundPolarity','dark','Sensitivity',0.4);
            BW = imcomplement(BW);            
            ax2=subplot(1,3,2);
            myImagesc(app,ax2,BW);      
            title(ax2,'Imbinarise');
             
             ax3=subplot(1,3,3);
             BW=imclearborder(BW);      %Clear up borders            
             BW = bwareafilt(BW,[5000 100000]);   % Make sure no small areas are passed
             keep = bwareafilt(BW,10);            % Allow upto 10 largest objects to be kept
             keep = imfill(keep,"holes");         % Fill any holes
             myImagesc(app,ax3,keep);      
             title(ax3,'bwareafilt');
             S = regionprops(keep, 'Area','Centroid')
             [sy,~]=size(S)
             centroids=S.Centroid
             hold(ax2,'on');
             % cl = {'r+','b+','m+','r*','b*','m*','c+','c*'};
             for i=1:sy
                   xc=S(i).Centroid(:,1);    yc=S(i).Centroid(:,2);
                  ReportMessage(app,['Area ',num2str(i),' = ',num2str(S(i).Area),', xc=',num2str(xc,'%.1f'), ', yc=',num2str(yc,'%.1f')])
                  plot(ax2,xc,yc,'r+');   %  plot(ax2,xc,yc,cl{i}); 
             end

Thanks for any help

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Matt J 2023-1-23

I suggest attaching the input image IM in a .mat file, so that we can play with it.

Jason 2023-1-23

编辑：Jason 2023-1-24

IM.mat

Hi Matt, here you go.

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Answer 1

Image Analyst 2023-1-24

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链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1898565-identifying-blobs-and-area-filtering#answer_1155675

在 MATLAB Online 中打开

Try the attached.

% Demo by Image Analyst
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 = 16;
markerSize = 40;
%--------------------------------------------------------------------------------------------------------
%    READ IN TEST IMAGE
folder = [];
baseFileName = 'im.png';
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;
    end
end
grayImage = 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(grayImage)
if numberOfColorChannels > 1
    % It's not really gray scale like we expected - it's color.
    fprintf('It is not really gray scale like we expected - it is color\n');
    % Extract the blue channel.
    grayImage = rgb2gray(grayImage);
end
%--------------------------------------------------------------------------------------------------------
%    READ IN BACKGROUND IMAGE
folder = [];
baseFileName = 'im background.png';
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;
    end
end
backgroundImage = imread(fullFileName);
%--------------------------------------------------------------------------------------------------------
% Display the image.
subplot(2, 3, 1);
imshow(grayImage, []);
impixelinfo;
axis('on', 'image');
title('Original Gray Scale Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Update 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(grayImage)
% Maximize window.
g = gcf;
g.WindowState = 'maximized';
drawnow;
%--------------------------------------------------------------------------------------------------------
% Display the image.
subplot(2, 3, 2);
imshow(backgroundImage, []);
impixelinfo;
axis('on', 'image');
title('Background Image', 'FontSize', fontSize, 'Interpreter', 'None');
%--------------------------------------------------------------------------------------------------------
% Divide the two
correctedImage = double(grayImage) ./ double(backgroundImage);
%--------------------------------------------------------------------------------------------------------
% Display the image.
subplot(2, 3, 3);
imshow(correctedImage, []);
impixelinfo;
axis('on', 'image');
title('Background Corrected Image', 'FontSize', fontSize, 'Interpreter', 'None');
%--------------------------------------------------------------------------------------------------------
% Display histogram
subplot(2, 3, 4);
histogram(correctedImage);
grid on;
title('Histogram of Background Corrected Image', 'FontSize', fontSize, 'Interpreter', 'None');
%--------------------------------------------------------------------------------------------------------
% Threshold to create mask
mask = ~(correctedImage >= 0.9 & correctedImage <= 1.1);
% Get rid of blobs touching the border.
mask = imclearborder(mask);
% Take 6 largest blobs.
mask = bwareafilt(mask, 6);
% Fill the blobs.
mask = imfill(mask, 'holes');
subplot(2, 3, 5);
imshow(mask);
impixelinfo;
axis('on', 'image');
title('Mask Image with Centroids Marked', 'FontSize', fontSize, 'Interpreter', 'None');
%--------------------------------------------------------------------------------------------------------
% Get the areas, diameters, and centroids.
props = regionprops(mask, 'Area', 'Centroid', 'EquivDiameter');
allAreas = [props.Area]
allDiameters = [props.EquivDiameter]
xy = vertcat(props.Centroid);
% Plot centroids on image.
xCentroids = xy(:, 1);
yCentroids = xy(:, 2);
hold on;
plot(xCentroids, yCentroids, 'r+', 'LineWidth', 3, 'MarkerSize', 20)

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Image Analyst 2023-1-25

I have no idea where the boundaries are. You might have to manually trace it. See attached demos.

Jason 2023-1-25

Yep, I guessed it might be too difficult, but thanks anyway for sharing your examples

Jason

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Answer 2

Image Analyst 2023-1-23

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1898565-identifying-blobs-and-area-filtering#answer_1154065

BGCorrect_demo.m

I would try to get an image with no drops in it and then do a background correction by dividing by it. Then your global threshold will work better. See attached background correction demo.

And, see my Image Processing Tutorial in my File Exchange:

Image Analyst's File Exchange

If you need more help, attach your droplets image and your background image without any droplets in it with the paperclip icon.

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