Is my bar graph accurately graphing what I ask?

Question

Neo 2023-2-2

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1905531-is-my-bar-graph-accurately-graphing-what-i-ask

评论： Image Analyst 2023-2-3

i have an image which i have divided into 12 regions. I have made a code that I think counts the number of green dots in that image and plots them in a bar graph as function of the region in the image. is the code doing what i expect it to do? please correct or confirm.

First, the code converts the image (premask) into a gray image then applies a mask (screenshot). now that the mask is applied i want to count those specks as a function of their region because i want to see how the specks fluctate by number across the image in its differnt regions.

% count the graylevel specks and plot as a function of the region number (the once green specks).
    greenspots = (g<255);
    numberofgreenspots = numel(grayImage);
    [pixelCounts, grayLevels] = imhist(grayImage);
    %meanGL(k) = mean(grayImage(masksinusoid));
figure
bar(numberofgreenspots, 1:length(endingColumns));
grid on;
title('counting')
xlabel('green speck #')
ylabel('region #')

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Image Analyst 2023-2-3

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1905531-is-my-bar-graph-accurately-graphing-what-i-ask#answer_1163101

在 MATLAB Online 中打开

No, you'd need to do this

% count the graylevel specks and plot as a function of the region number (the once green specks).
for k = 1 : whatever
    greenSpotMask = g < 255; % g is the image of just this strip only.
    % Count pixels.
    areaOfGreenSpots(k) = nnz(greenSpotMask)
    % Count number of contiguous regions.
    [~, numberOfGreenSpots(k)] = bwlabel(greenSpotMask);
    % Display histogram of strip.
    [pixelCounts, grayLevels] = imhist(g);
    %meanGL(k) = mean(grayImage(masksinusoid));
end
figure
bar(numberOfGreenSpots);
grid on;
title('Counting of Green Spots per Strip Region')
xlabel('Region #')
ylabel('Number of green spots in the region')

9 个评论
显示 7更早的评论隐藏 7更早的评论

Neo 2023-2-3

编辑：Image Analyst 2023-2-3

在 MATLAB Online 中打开

Using one of your previous answers as a reference:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;
%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = 'hi.jpg';
folder = pwd;
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
%=======================================================================================
% Read in image.
rgbImage = imread(fullFileName);
% Get the dimensions of the image.
[rows, columns, numberOfColorChannels] = size(rgbImage)
% Display image.
subplot(2, 3, 1);
imshow(rgbImage, []);
impixelinfo;
axis on;
caption = sprintf('Original RGB Image\n%s', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Set up figure properties:
% Enlarge figure to full screen.
g = gcf;
g.WindowState = "maximized";
% 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', 'Spatial Phenomics in Matlab', 'NumberTitle', 'Off')
drawnow;
%--------------------------------------------------------------------------------------------------
% Get the green channel
grayImage = rgbImage(:, :, 2);
% Display image.
subplot(2, 3, 2);
imshow(grayImage, []);
impixelinfo;
axis on;
title('Green Channel', 'FontSize', fontSize, 'Interpreter', 'None');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
drawnow;
%--------------------------------------------------------------------------------------------------
% Show the histogram
subplot(2, 3, 3);
imhist(grayImage);
grid on;
drawnow;
%--------------------------------------------------------------------------------------------------
% Create a logical image mask of the green parts.
lowThreshold = 14;
highThreshold = 255;
% [lowThreshold, highThreshold, lastThresholdedBand] = threshold(3, 255, grayImage);
masksinusoid = grayImage >= lowThreshold & grayImage <= highThreshold;
% Display image.
subplot(2, 3, 4);
imshow(masksinusoid, []);
impixelinfo;
axis on;
title('Initial Mask of Green Areas', 'FontSize', fontSize, 'Interpreter', 'None');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
drawnow;
%--------------------------------------------------------------------------------------------------
% Get the mean of the green pixels
%meanGreen = mean(grayImage(mask))
% Get mean across 12 vertical bands of the image
startingColumns = round(linspace(1, columns+1, 13))
endingColumns = startingColumns(2:end) - 1
for k = 1 : length(endingColumns)
    col1 = startingColumns(k);
    col2 = endingColumns(k);
    % Make a strip
    mask = false(size(masksinusoid));
    mask(:, col1:col2) = true;
    subplot(1, 3, 2);
    imshow(mask);
    impixelinfo;
    axis('on', 'image');
    caption = sprintf('Bin #%d', k);
    title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
    % Crop the image so we get the image in the mask
    subImage = masksinusoid(:, col1 : col2);
    subplot(1, 3, 3);
    imshow(subImage);
    impixelinfo;
    axis('on', 'image');
    caption = sprintf('Subimage #%d', k);
    title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
    drawnow;
    % Make measurements of mean graylevel.
    %meanGL(k) = mean(grayImage(masksinusoid));
end
% count the graylevel specks and plot as a function of the region number (the once green specks).
for k = 1 : length(endingColumns)
    greenSpotMask = g < 255; % g is the image of just this strip only.
    % Count pixels.
    areaOfGreenSpots(k) = nnz(greenSpotMask)
    % Count number of contiguous regions.
    [~, numberOfGreenSpots(k)] = bwlabel(greenSpotMask);
    % Display histogram of strip
    [pixelCounts, grayLevels] = imhist(masksinusoid);
end
figure
bar(numberOfGreenSpots);
grid on;
title('Counting of Green Spots per Strip Region')
xlabel('Region #')
ylabel('speck #')

Image Analyst 2023-2-3

在 MATLAB Online 中打开

Yeah because you did lots of stuff wrong. Like the whole second loop, and not using the correct mask, etc.. Corrected code is below.

% Demo by Image Analyst
clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;
%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = 'hi.jpg';
folder = pwd;
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
%=======================================================================================
% Read in image.
rgbImage = imread(fullFileName);
% Get the dimensions of the image.
[rows, columns, numberOfColorChannels] = size(rgbImage)
% Display image.
subplot(2, 3, 1);
imshow(rgbImage, []);
impixelinfo;
axis on;
caption = sprintf('Original RGB Image\n%s', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Set up figure properties:
% Enlarge figure to full screen.
g = gcf;
g.WindowState = "maximized";
% 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', 'Spatial Phenomics in Matlab', 'NumberTitle', 'Off')
drawnow;
%--------------------------------------------------------------------------------------------------
% Get the green channel
grayImage = rgbImage(:, :, 2);
% Display image.
subplot(2, 3, 2);
imshow(grayImage, []);
impixelinfo;
axis on;
title('Green Channel', 'FontSize', fontSize, 'Interpreter', 'None');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
drawnow;
%--------------------------------------------------------------------------------------------------
% Show the histogram
subplot(2, 3, 3);
imhist(grayImage);
grid on;
drawnow;
%--------------------------------------------------------------------------------------------------
% Create a logical image mask of the green parts.
lowThreshold = 14;
highThreshold = 255;
% [lowThreshold, highThreshold, lastThresholdedBand] = threshold(3, 255, grayImage);
masksinusoid = grayImage >= lowThreshold & grayImage <= highThreshold;
% Display image.
subplot(2, 3, 4);
imshow(masksinusoid, []);
impixelinfo;
axis on;
title('Initial Mask of Green Areas', 'FontSize', fontSize, 'Interpreter', 'None');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
drawnow;
%--------------------------------------------------------------------------------------------------
% Get the mean of the green pixels
%meanGreen = mean(grayImage(mask))
% Get mean across 12 vertical bands of the image
startingColumns = round(linspace(1, columns+1, 13))
endingColumns = startingColumns(2:end) - 1
for k = 1 : length(endingColumns)
    col1 = startingColumns(k);
    col2 = endingColumns(k);
    % Make a strip
    mask = false(size(masksinusoid));
    mask(:, col1:col2) = true;
    subplot(1, 3, 2);
    imshow(mask);
    impixelinfo;
    axis('on', 'image');
    caption = sprintf('Bin #%d', k);
    title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
    % Crop the mask image so we get the mask only in the strip zone.
    stripMaskImage = masksinusoid(:, col1 : col2);
    subplot(1, 3, 3);
    imshow(stripMaskImage);
    impixelinfo;
    axis('on', 'image');
    caption = sprintf('Mask in Subimage strip #%d', k);
    title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
    drawnow;
    % Make measurements of mean graylevel.
    %meanGL(k) = mean(grayImage(masksinusoid));
    % Count pixels.
    areaOfGreenSpots(k) = nnz(stripMaskImage);
    % Count number of contiguous regions.
    [~, numberOfGreenSpots(k)] = bwlabel(stripMaskImage);
end
% Wrong code commented out below.
% % count the graylevel specks and plot as a function of the region number (the once green specks).
% for k = 1 : length(endingColumns)
%     greenSpotMask = g < 255; % g is the image of just this strip only.
%     % Count pixels.
%     areaOfGreenSpots(k) = nnz(greenSpotMask)
%     % Count number of contiguous regions.
%     [~, numberOfGreenSpots(k)] = bwlabel(greenSpotMask);
%     % Display histogram of strip
%     [pixelCounts, grayLevels] = imhist(masksinusoid);
% end
figure
subplot(1, 2, 1);
bar(numberOfGreenSpots);
grid on;
title('Count of Green Spots per Strip Region')
xlabel('Region #')
ylabel('speck #')
subplot(1, 2, 2);
bar(areaOfGreenSpots);
grid on;
title('Area of Green Spots per Strip Region')
xlabel('Region #')
ylabel('speck #')

Neo 2023-2-3

@Image Analyst

So i can understand your though process better, why did you plot them seperatley?

Image Analyst 2023-2-3

They represent totally different things and have different ranges. The number of pixels might be in the hundreds of thousands and the number might be a few dozen or hundred. You'd need at least 2 y axes, using yyaxis(), to plot them on the same plot. Like I said, the number of spots, like what you names the variable at the beginning, is most likely not what you want. You probably want the number of pixels (which is the area).

请先登录，再进行评论。

Is my bar graph accurately graphing what I ask?

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

采纳的回答

9 个评论
显示 7更早的评论隐藏 7更早的评论

更多回答（0 个）

另请参阅

类别

标签

Community Treasure Hunt

Is my bar graph accurately graphing what I ask?

0 个评论 显示 -2更早的评论隐藏 -2更早的评论

采纳的回答

9 个评论 显示 7更早的评论隐藏 7更早的评论

更多回答（0 个）

另请参阅

类别

标签

Community Treasure Hunt

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

9 个评论
显示 7更早的评论隐藏 7更早的评论