Identifying blobs and area filtering
显示 更早的评论
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
2 个评论
Matt J
2023-1-23
I suggest attaching the input image IM in a .mat file, so that we can play with it.
采纳的回答
Image Analyst
2023-1-24
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)
5 个评论
Jason
2023-1-25
Image Analyst
2023-1-25
You're welcome. Thanks for accepting. I had to create the background image in Photoshop from the original image but you'll just snap an image with no droplets in there and save that as your background image.
Jason
2023-1-25
Hi, not sure if I should start another thread or not.....
Any idea about getting the preimeter of this drop. I've spent all day playing with thresholds, areafilters etc, but just can't get it. (Its the larger outer circle perimeter that I need to get the area of)
Thanks for any pointers
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
更多回答（1 个）
Image Analyst
2023-1-23
0 个投票
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.
If you need more help, attach your droplets image and your background image without any droplets in it with the paperclip icon.
类别
在 帮助中心 和 File Exchange 中查找有关 Convert Image Type 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!
Translated by 
