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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

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