How to compare two matrix?
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redChannel = IM(:, :, 1);
greenChannel = IM(:, :, 2);
blueChannel = IM(:, :, 3);
for yourNumber = 1 : max(labelimg(:))
thisLabel = labelimg == yourNumber; % for example 2 or 3 or whatever region you want.
meanR(yourNumber) = mean(redChannel(thisLabel));
meanG(yourNumber) = mean(greenChannel(thisLabel));
meanB(yourNumber) = mean(blueChannel(thisLabel));
end
table(neigbor label)=
2 3 4 5
2 1
3 1 1
4 1 1 1
5 1 0 1 1
I got a table which show the neighbor label and I got mean rgb for each label, I just need loop through the left triangle because another part is same.
The mean value for the label is double type, how I can round to integer only?
I got the mean of each label region and then I now want to compare them.
for i=2 : max(table(:))
for j=2:max(table(:))
if(i,j+1)=1 %1 mean 2 label are neighbor
if compare(j+1,i)<=(rgb+-5) %then reassign the label
if (i>j+1) label i = label j+1 %always assign to smaller label
else label j+1 = label to i
Final result I hope to get is like this
label 4 and 5 is within(rgb+-5) with label 2 so all assign to label 2
label =
3 3 3 3 3 3
1 1 1 1 1 1
1 2 2 1 4 1
1 1 1 1 4 1
5 5 5 1 1 1
5 5 5 5 5 5
result =
3 3 3 3 3 3
1 1 1 1 1 1
1 2 2 1 2 1
1 1 1 1 2 1
2 2 2 1 1 1
2 2 2 2 2 2
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채택된 답변
Walter Roberson
2015년 12월 6일
abs(meanR(j+1)-meanR(i)) <= 5 &&
abs(meanB(j+1)-meanB(i)) <= 5 &&
abs(meanG(j+1)-meanG(i)) <= 5
댓글 수: 4
Walter Roberson
2015년 12월 7일
maxlab = max(label(:));
for i = 1 : maxlab
for j = 1 : maxlab - 1
if table(i,j+1) == 1
if abs(meanR(j+1)-meanR(i)) <= 5 &&
abs(meanB(j+1)-meanB(i)) <= 5 && abs(meanG(j+1)-meanG(i))
<= 5
if label(i, j+1) > label(i, j)
label(i, j+1) = label(i,j)
else
label(i,j) = label(i, j+1);
end
end
end
end
추가 답변 (1개)
Image Analyst
2015년 12월 6일
The answer to "how I can round to integer only?" is to use the int32() function.
댓글 수: 5
Image Analyst
2015년 12월 6일
I have no idea what that triangular table is so I can't answer. And I don't know what reassigning labels is going to do. I think you're trying to do some kind of region growing/merging because you started out with a bad segmentation that was made worse by oversegmentation by watershed and now you're trying to fix it in a way that won't work.
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