MATLAB: Automatically segment the fish eye

fishfish eyesimage segmentationsegmentation

Hi, I'm having trouble with the segmentation of fish eye

I follow the instruction from this: https://www.mathworks.com/help/images/detecting-a-cell-using-image-segmentation.html?fbclid=IwAR3MPi9mlL6Rt8R7sA20oyZdvoiMhIpxpW-dxjSUfmoNcX-g9u2_5cn6V3Y

I changed some parameters and successfully segmented the fish eye like the image I attached.

However, for the fish that is stale like the image attached, the code couldn't segment the eye.

Can anyone help me to solve the problem ? And how can I segment the fish eye successfully in any situation (Fresh and stale fishes) ?

Thanks in advance.

Here is my code:

I = imread('');
I = imresize(I,[500 500]);
I = rgb2gray(I);
[~,threshold] = edge(I,'sobel');
fudgeFactor = 1;
BWs = edge(I,'sobel',threshold * fudgeFactor);
figure
imshow(BWs)
title('Binary Gradient Mask')
se90 = strel('line',1,90);
se0 = strel('line',1,0);
BWsdil = imdilate(BWs,[se90 se0]);
figure
imshow(BWsdil)
title('Dilated Gradient Mask')
BWdfill = imfill(BWsdil,'holes');
figure
imshow(BWdfill)
title('Binary Image with Filled Holes')
BWnobord = imclearborder(BWdfill,4);
figure
imshow(BWnobord)
title('Cleared Border Image')
seD = strel('diamond',1);
BWfinal = imerode(BWnobord,seD);
BWfinal = imerode(BWfinal,seD);
figure
imshow(BWfinal)
title('Segmented Image');
BWmask = labeloverlay(I,BWfinal);
figure
imshow(BWmask)
title('Mask Over Original Image')
BWoutline = bwperim(BWfinal);
Segout = I; 
Segout(BWoutline) = 255; 
figure
imshow(Segout)
title('Outlined Original Image')
maskedGrayImage = bsxfun(@times, I, cast(BWfinal, 'like', I));
figure
imshow(maskedGrayImage)

Best Answer

Try this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clearvars;
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;
%=======================================================================================
% Have user browse for a file, from a specified "starting folder."
% For convenience in browsing, set a starting folder from which to browse.
% startingFolder = pwd;  % or 'C:\wherever';
% if ~exist(startingFolder, 'dir')
% 	% If that folder doesn't exist, just start in the current folder.
% 	startingFolder = pwd;
% end

% % Get the name of the file that the user wants to use.
% defaultFileName = fullfile(startingFolder, 'n*.*');
% [baseFileName, folder] = uigetfile(defaultFileName, 'Select a file');
% if baseFileName == 0
% 	% User clicked the Cancel button.
% 	return;
% end
folder = pwd;
baseFileName = 'IMG_Segment_Failed.JPG';
% baseFileName = 'IMG_Segment_Success.JPEG';
fullFileName = fullfile(folder, baseFileName);
rgbImage = imread(fullFileName);
% Get the dimensions of the image.
[rows1, columns1, numberOfColorChannels1] = size(rgbImage)
% Display the original image.
subplot(2, 2, 1);
imshow(rgbImage, []);
axis('on', 'image');
caption = sprintf('Original Color Image\n"%s"', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.



% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0.05 1 0.95]);
% 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 Image Analyst', 'NumberTitle', 'Off')
[mask, maskedRGBImage] = createMask(rgbImage);
% Display the image.

subplot(2, 2, 2);
imshow(mask, []);
axis('on', 'image');
title('Initial Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Do area filtering.
mask = bwareafilt(mask, [30000, 60000]);
% Display the image.
subplot(2, 2, 3);
imshow(mask, []);
axis('on', 'image');
title('Mask Image after area filtering', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Measure things in the mask
labeledImage = bwlabel(mask);
props = regionprops(labeledImage, 'Area', 'Perimeter');
allAreas = [props.Area];
% sortedAreas = sort(allAreas)
allPerims = [props.Perimeter];
circularities = allPerims .^ 2 ./ (4 * pi * allAreas)
subplot(2, 2, 4);
% histogram(circularities);
% grid on;
% Extract the roundest blob - the one with circularity closest to 1
[~, index] = min(abs(circularities - 1))
mask = ismember(labeledImage, index);
imshow(mask, []);
axis('on', 'image');
title('Mask Image after circularity filtering', 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
function [BW,maskedRGBImage] = createMask(RGB)
%createMask  Threshold RGB image using auto-generated code from colorThresholder app.
%  [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
%  auto-generated code from the colorThresholder app. The colorspace and
%  range for each channel of the colorspace were set within the app. The
%  segmentation mask is returned in BW, and a composite of the mask and
%  original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 19-Dec-2019
%------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.254;
channel1Max = 0.991;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.000;
channel2Max = 1.000;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.000;
channel3Max = 0.523;
% Create mask based on chosen histogram thresholds
sliderBW = (I(:,:,1) >= channel1Min ) & (I(:,:,1) <= channel1Max) & ...
	(I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
	(I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image.
maskedRGBImage = RGB;
% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end

It might need some tweaking to get it to work with all images.

Or you could try deep learning. I tried imfindcircles() and was not very successful with that function.

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MATLAB: Obtain average image threshold without the background

Try this:

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 = 22;
%--------------------------------------------------------------------------------------------------------

%    READ IN IMAGE
folder = pwd;
baseFileName = 'image.png';
% 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;
	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.
	% Use weighted sum of ALL channels to create a gray scale image.
	grayImage = rgb2gray(grayImage);
	% 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 = grayImage(:, :, 2); % Take green channel.
end
% Display the image.
subplot(2, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
%--------------------------------------------------------------------------------------------------------
%    SEGMENTATION OF IMAGE
% Get a binary image of just the blob and not including the black background or the white surround.
mask = grayImage > 0 & grayImage < 255;  %imbinarize(grayImage);
subplot(2, 2, 2);
imshow(mask, []);
impixelinfo;
title('Initial Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
% Display histogram of image but only the image within the mask
subplot(2, 3, 4);
histogram(grayImage(mask), 0:255);
grid on;
title('Histogram of gray image', 'FontSize', fontSize);
% Now get the threshold
thresh = 255 * graythresh(grayImage(mask))
% Put a red line there at the threshold
xline(thresh, 'Color', 'r', 'LineWidth', 2);
% Get a binary image of the bright stuff
brightStuff = grayImage >= thresh & mask;
subplot(2, 3, 5);
imshow(brightStuff, []);
impixelinfo;
title('Bright Pixels in Region', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
subplot(2, 3, 6);
darkStuff = ~brightStuff & mask;
imshow(darkStuff, []);
impixelinfo;
title('Dark Pixels in Region', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;

MATLAB: How to draw a BoundingBox

Hello,

I'm not sure in what state are your images after image preprocessing but this is what I used in similar problem with drawing bounding boxes.

imshow(YOUR_IMAGE);
hold on;
labeledImage = logical(YOUR_BINARY_IMAGE); %not needed, image should be already in logical
measurements = regionprops(labeledImage, 'BoundingBox');
for k = 1 : length(measurements)
    thisBB = measurements(k).BoundingBox;
    rectangle('Position',[thisBB(1),thisBB(2),thisBB(3),thisBB(4)],'EdgeColor','b','LineWidth',1 );
end

Best Answer

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MATLAB: Obtain average image threshold without the background

MATLAB: How to draw a BoundingBox

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