MATLAB: Locate points inside region based on coordinates

coordinatepixel coordinateregion

Hi guys, MATLAB rookie here. I have a matrix of points distribution coordinates and binary image of a structure. What I want to do is to select the points that located inside the structure of the binary image and extract those points. I read about using "&" but clearly it didn't work when I try it. Could you guys share some insights?

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doc inpolygon.

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First let's load the image into a usable format. You already have code to get binaryImage, so you can use that.

%% read image

I=imread('filled image.jpg');
I=I(29:540,84:595,1);%cut out border

binaryImage=I>128;

Method 1 will probably not have a good performance, but as an approximation you could loop through the rows of the filled image and find the mean position.

result = false(size(binaryImage));
for row=1:size(binaryImage,1)
    if any(binaryImage(row,:))%correct for empty lines in the image



        ind=round(mean(find(binaryImage(row,:))));
        result(row, ind)=true;
    end
end

You can improve on this method by using bwdist on the flipped image and find the maximum value in each row. You can use the second output of the max function to improve performance by avoiding a loop. Because an IM(1:3,[2 1 3]) style syntax will set 9 elements, not 3, we need linear indices. We also need to correct for empty lines in the image, where max will return 1.

dist2edge=bwdist(~binaryImage);
result = false(size(binaryImage));
[~,ind]=max(dist2edge,[],2);
rowSub=(1:size(result,1))';%transpose to make the shape match ind

colSub=ind;
linind=sub2ind(size(result), rowSub, colSub);
result(linind)=true;
result(~binaryImage)=false;%correct for empty lines in the image

In summary, with a display section:

%% read image
I=imread('filled image.jpg');
I=I(29:540,84:595,1);%cut out border
binaryImage=I>128;
%% method 1
result = false(size(binaryImage));
for row=1:size(binaryImage,1)
    if any(binaryImage(row,:))%correct for empty lines in the image
        ind=round(mean(find(binaryImage(row,:))));
        result(row, ind)=true;
    end
end
method1=result;
%% method 2
dist2edge=bwdist(~binaryImage);
result = false(size(binaryImage));
[~,ind]=max(dist2edge,[],2);
rowSub=(1:size(result,1))';%transpose to make the shape match ind
colSub=ind;
linind=sub2ind(size(result), rowSub, colSub);
result(linind)=true;
result(~binaryImage)=false;%correct for empty lines in the image
method2=result;
%% display
merged1=cat(3,binaryImage,method1,false(size(binaryImage)));
merged1=double(merged1);
merged2=cat(3,binaryImage,method2,false(size(binaryImage)));
merged2=double(merged2);
figure(1),clf(1)
subplot(2,3,[1 4])
imshow(binaryImage)
title('binary image')
subplot(2,3,2)
imshow(method1)
title('skeletonized image (method 1)')
subplot(2,3,3)
imshow(merged1)
title('merged image (method 1)')
subplot(2,3,5)
imshow(method2)
title('skeletonized image (method 2)')
subplot(2,3,6)
imshow(merged2)
title('merged image (method 2)')

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MATLAB: Changing the pixel value of a region defined by its contour points

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