Why my binary mask show only 0 value?

2 ビュー (過去 30 日間)
Dayangku Nur Faizah Pengiran Mohamad
Dayangku Nur Faizah Pengiran Mohamad 2023 年 10 月 4 日
コメント済み: dpb 2023 年 11 月 8 日
Here's my codes:
fontSize = 16;
I=imread('cropa8.png');
subplot(1, 2, 1);
imshow(I, []);
axis('on', 'image');
drawnow;
hp = impixelinfo();
hFig1 = gcf;
hFig1.Units = 'Normalized';
hFig1.WindowState = 'maximized';
hFig1.Name = 'Demo by Image Analyst';
hsvImage = rgb2hsv(I);
mask = hsvImage(:,:,2) > 0.3;
mask = imfill(mask, 'holes');
subplot(1, 2, 2);
imshow(mask, []);
axis('on', 'image');
drawnow;
hp = impixelinfo();
subplot(1, 2, 1);
boundaries = bwboundaries(mask);
numberOfBoundaries = size(boundaries, 1);
hold on;
for k = 1 : numberOfBoundaries
thisBoundary = boundaries{k};
x = thisBoundary(:,2);
y = thisBoundary(:,1);
plot(x, y, 'g-', 'LineWidth', 3);
imwrite(logical(mask),'maska8.png');
end
hold off;
axis('on', 'image');
As below shown is my result value in logical mask only shown 0 value.
And this my data image, which is 512x512x3 uint8.
Can someone help me, why my image after convert into binary mask only shown in 0 value?

採用された回答

dpb
dpb 2023 年 10 月 4 日
編集済み: dpb 2023 年 11 月 8 日
fontSize = 16;
I=imread('cropa8.png');
subplot(1, 2, 1);
imshow(I, []);
axis('on', 'image');
drawnow;
hp = impixelinfo();
hFig1 = gcf;
hFig1.Units = 'Normalized';
hFig1.WindowState = 'maximized';
hFig1.Name = 'Demo by Image Analyst';
hsvImage = rgb2hsv(I);
mask = hsvImage(:,:,2) > 0.3;
any(mask,'all')
ans = logical
1
mask = imfill(mask, 'holes');
any(mask,'all')
ans = logical
1
subplot(1, 2, 2);
imshow(mask, []);
axis('on', 'image');
drawnow;
hp = impixelinfo();
subplot(1, 2, 1);
boundaries = bwboundaries(mask);
numberOfBoundaries = size(boundaries, 1);
hold on;
for k = 1 : numberOfBoundaries
thisBoundary = boundaries{k};
x = thisBoundary(:,2);
y = thisBoundary(:,1);
plot(x, y, 'g-', 'LineWidth', 3);
imwrite(logical(mask),'maska8.png');
end
nnz(mask)
ans = 8968
r1=find(any(mask,2),1), r2=find(any(mask,2),1,'last')
r1 = 21
r2 = 159
c1=find(any(mask),1), c2=find(any(mask),1,'last')
c1 = 277
c2 = 365
mask(min(r1-5,r2+5):max(r1-5,r2+5),min(c1,c2)-5:max(c1,c2)+5)
ans = 149×99 logical array
Columns 1 through 49 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 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0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Column 99 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
hold off;
axis('on', 'image');
M=mask(min(r1,r2):max(r1,r2),min(c1,c2):max(c1,c2));
whos M
Name Size Bytes Class Attributes M 139x89 12371 logical
figure,imshow(ans,[])
You're just not looking in the right place...
  4 件のコメント
Dayangku Nur Faizah Pengiran Mohamad
Dayangku Nur Faizah Pengiran Mohamad 2023 年 11 月 8 日
Ok Sir, I get now thanks and one more question. I have saved the last image result that you obtained. Is it the image sizes is 577x433 px? How can I get the exact area like this but with in 512x512 px without losing information quality of the image?
dpb
dpb 2023 年 11 月 8 日
Why don't you use size() on the result and see intead of guessing?
But, no, it certainly isn't that; don't know how you came up with those values at all...see the little addition to the previous answer at the bottom that looks like
%M=mask(min(r1,r2):max(r1,r2),min(c1,c2):max(c1,c2));
%whos M
%Name Size Bytes Class Attributes
%M 139x89 12371 logical
shows that the bounds of the mask area is a subsection of the total image that is 139x89; the plotted version is 10 larger in each direction since I added a 5-pixel border.
The original image is 512x512 and you've only taken a very small piece of it; it can't possibly be 512x512 and you have all the information there is; if you mean to blow the mask itself up to 512x512, you'll have to scale it up by
512./[139 89]
ans = 1×2
3.6835 5.7528
which is quite a large magnification and it's going to get really jaggedy around the edges as it already is somewhat that way.
I'm not an image processing guy; there are undoubtedly ways to try to do such magnifications with smoothing, but those techniques are beyond my ken, sorry.

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