Detecting and counting the number of scales (circular or psuedo circular objects in the image) and drawing boundaries around the scales or circular objects.

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Atreya Danturthi
Atreya Danturthi 2021-7-30
评论： Atreya Danturthi 2021-7-31
I have asked this question previously one the forum and got a few answers for the same, however they do not really answer the core aspects of what I want to solve. So, I am asking a modified version of the same question again.
I have multiple grayscale images, which have circular or psuedo circular objects within them. I need to detect them, draw boundaries around them and then count the number of these objects in each image.
I am attaching one grayscale image for your reference.
Any inputs will be highly appreciated.
This is the code that I had tried out.
Guys, can anyone give any suggestions, I would really appreciate some help as I am on a ticking clock.
I have attached the photos with objects marked in red.
X = imread("f_000047.tif");
% Adjust data to span data range.
X = imadjust(X);
X = imgaussfilt(X,1.4);
% Threshold image - manual threshold
BW = X > 164;
% Create masked image.
fontSize = 8;
maskedImage = X;
maskedImage(~BW) = 0;
SE = strel("disk",7); % Generating a disk-type structuring element of radius 10 for dilation
maskedImage = imdilate(maskedImage,SE); %Filling up holes or inaccuracies in the intial BGMask
%maskedImage = imrotate(maskedImage,-90);
subplot(3,1,1);
imshow(maskedImage);
title("MaskedImage","FontSize",fontSize);
%----------------------------------------------------------------------------------------------------------
%Finding out higher SD regions across the background
ImgSD = stdfilt(X,ones(13)); %Standard deviation (SD) filtering based on varying SDs across the image
ImgSD(~maskedImage)=0; %Removing the background
subplot(3,2,2);
imshow(ImgSD,[]);
subplot(3,2,3);
histogram(ImgSD,100);
[x,y] = size(ImgSD);
xGrad = zeros(x,y);%Horizontal gradient matrix definition
yGrad = zeros(x,y);%Vertical gradient matrix definition
Tan_ver_add = size(x,y);
Tan_horz_add = size(x,y);
Tan_ver_sub = size(x,y);
Tan_horz_sub = size(x,y);
for i = 1:x-1
for j = 2:y-1
xGrad(i,j) = (ImgSD(i,j+1)-ImgSD(i,j-1))/2; % finding the horizontal gradient across the image (Method 1)
end
end
h_grad = (circshift(ImgSD,[0,1])-circshift(ImgSD,[0,-1]))/2; %Method 2
for j = 1:y-1
for i = 2:x-1
yGrad(i,j) = (ImgSD(i+1,j)-ImgSD(i-1,j))/2; % finding the vertical gradient across the image (Method 1)
end
end
v_grad = (circshift(ImgSD,[1,0])-circshift(ImgSD,[-1,0]))/2; %Method 2
%-----------------------------------------------------------------------------------------------
%Gradient Modulus
grad_tot_mod =sqrt((h_grad).^2+(v_grad).^2); % finding the magnitude of gradient across the image (Method 2)
GradMod = sqrt((xGrad).^2+(yGrad).^2); %Method 2 for Gradient Modulus
%---------------------------------------------------------------------------------------------
%Calculating double derivative in the horizontal and vertical directions as
%a second parameter for reducing the area of interest
double_der_h = zeros(x,y); %Horizontal double derivative matrix definition
double_der_v = zeros(x,y); %Vertical double derivative matrix definition
for i = 1:x-1
for j = 2:y-1
double_der_h(i,j) = (ImgSD(i,j+1)-2*ImgSD(i,j)+ImgSD(i,j-1)); % finding double derivative across x-direction in the image
end
end
for j = 1:y-1
for i = 2:x-1
double_der_v(i,j) = (ImgSD(i+1,j)-2*ImgSD(i,j)+ImgSD(i-1,j)); % finding double derivative across y-direction in the image
end
end
double_der_tot = double_der_h+double_der_v;% Can we do scalar addition of the individual components of the double derivative or do we need to calculate the modulus
%Should I use a Laplacian operator instead?
%doubleDMod = sqrt((double_der_h).^2+(double_der_v).^2);
subplot(3,3,1);
imshow(X);
hold on
for i = 1:x
for j = 1:y
if (grad_tot_mod(i,j)>0.1 && grad_tot_mod(i,j)<10) %imposing the gradient condition to plot markers
if (double_der_tot(i,j)~=0) % imposing double derivative condition to plot markers %Ask about a different condition >=0
if ImgSD(i,j)>=0
Tan_horz_add= atan2d(h_grad(i+5,j),v_grad(i+5,j));
Tan_horz_sub= atan2d(h_grad(i-5,j),v_grad(i-5,j));
Tan_ver_add= atan2d(h_grad(i,j+5),v_grad(i,j+5));
Tan_ver_sub= atan2d(h_grad(i,j-5),v_grad(i,j-5));
%Changed the angle definition from
%(v_grad(),h_grad()) to (h_grad(),v_grad())
if Tan_horz_add<0
Tan_horz_add= Tan_horz_add+180;
end
if Tan_ver_add < 0
Tan_ver_add = Tan_ver_add+180;
end
if Tan_horz_sub < 0
Tan_horz_sub = Tan_horz_sub+180;
end
if Tan_ver_sub < 0
Tan_ver_sub = Tan_ver_sub+180;
end
if ((abs(Tan_ver_add-Tan_ver_sub)>= 5 && abs(Tan_ver_add-Tan_ver_sub)<15)||(abs(Tan_ver_add-Tan_ver_sub)>=95 && abs(Tan_ver_add-Tan_ver_sub)<120))
if ((abs(Tan_horz_add-Tan_horz_sub)>=5 && abs(Tan_horz_add-Tan_horz_sub)<15))
plot(i,j,"*")
end
end
end
end
end
end
end
hold off
  8 个评论
显示 6更早的评论
Image Analyst
Image Analyst 2021-7-31
编辑：Image Analyst 2021-7-31
It works fine with gray scale images. Here's proof:
grayImage = imread('cameraman.tif');
imshow(grayImage, []);
drawnow;
g = gcf;
g.WindowState = 'maximized'
uiwait(msgbox('Draw a freehand curve'));
h = drawfreehand
% Rplace by a curve.
xy = h.Position;
x = xy(:, 1);
y = xy(:, 2);
% Tack first point onto last so the curve will be closed.
x = [x; x(1)];
y = [y; y(1)];
hold on;
delete(h);
plot(x, y, 'y-', 'LineWidth', 3);
Atreya Danturthi
Atreya Danturthi 2021-7-31
"Error using images.internal.imageDisplayValidateParams>validateCData (line 118)
Multi-plane image inputs must be RGB images of size MxNx3.
Error in images.internal.imageDisplayValidateParams (line 30)
common_args.CData = validateCData(common_args.CData,image_type);
Error in images.internal.imageDisplayParseInputs (line 79)
common_args = images.internal.imageDisplayValidateParams(common_args);
Error in imshow (line 253)
images.internal.imageDisplayParseInputs({'Parent','Border','Reduce'},preparsed_varargin{:});
Error in Freehandmethod (line 2)
imshow(grayImage, []);
This is the error that showed up when I replaced the cameraman image with one of my images.

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