How to crop a masked area (polygon shape) out of an image?
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Hi all,
Now my code is like below:
I = imread('moon.tif');
figure;
imshow(I)
Poly_Mask = images.roi.Polygon(gca,'Position',[100 150; 200 250; 300 350; 150 450]);
As you can see, the example image is now masked with a polygon shape. I would like to crop the masked area (polygon shape) out of the image. Could you please suggest me how to do this? Thank you.
0 件のコメント
採用された回答
Image Analyst
2022 年 3 月 30 日
Try this:
grayImage = imread('moon.tif');
[rows, columns, numberOfColorChannels] = size(grayImage)
subplot(2, 1, 1);
imshow(grayImage, []);
axis('on', 'image');
title('Original Image')
x = [100, 200, 300, 150];
y = [150, 250, 350, 450];
% tack on starting point to close it so the plot is not oepn jaw. (Only
% needed if you wan to plot the outline in the overlay.
x = [x, x(1)];
y = [y, y(1)];
hold on;
plot(x, y, 'r-', 'LineWidth', 2);
mask = poly2mask(x, y, rows, columns);
% Erase outside mask by setting to zero
grayImage(~mask) = 0;
% Crop
croppedImage = grayImage(min(y):max(y), min(x):max(x));
subplot(2, 1, 2);
imshow(croppedImage)
axis('on', 'image');
title('Cropped Image')
2 件のコメント
Image Analyst
2022 年 3 月 30 日
You can't make it transparent, and it does not need to be for any reason that I can think of, certainly not for normxcorr2().
You can have any shape you want just by putting in the coordinates of the shape boundaries into poly2mask().
その他の回答 (1 件)
Tala
2022 年 3 月 29 日
編集済み: Tala
2022 年 3 月 29 日
I cannot see your image. But I used a photo of my dog (because she wont sue me :D) to show the concept:
I=rgb2gray(imread("Tala1.jpg"));
x=[100 200 300 150];% your ROI x values
y=[150 250 350 450];% your ROI y values
[rows, columns,~] = size(I);
mask = imcomplement(poly2mask(x, y, rows, columns));
mul = immultiply(I,mask);
imshow(mul)
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/945549/image.jpeg)
3 件のコメント
Tala
2022 年 3 月 30 日
編集済み: Tala
2022 年 3 月 30 日
do you need to crop a polygon? you could crop out a rectangular section of image with imcrop(I, [x y dx dy]) and then calculate corrolation or convolution for feature matching.
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