how to detect background color of image ?
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i want to make function, so if the background color if black like image 1, it will change to white.
But, if the background color image is white like in image 2, so it doesn't change.
How to make it ?? thanks
1 个评论
MJ Thangaraj
2016-4-23
The image is Binary so it's obviously going to have only White and BLACK values.Check whether the background in white and then Complement the image .
采纳的回答
Image Analyst
2016-4-23
If you can make the assumption that the majority of the pixels in the image are the background color, then
[rows, columns] = size(binaryImage);
numWhitePixels = sum(binaryImage);
numBlackPixels = rows * columns - numWhitePixels;
if numWhitePixels > numBlackPixels
% Background is white.
% Do nothing at all.
else
% Background is black.
% Make image all white, everywhere at every pixel.
binaryImage(:) = true;
end
5 个评论
Image Analyst
2016-4-24
OK, then this should do it
bw = ~bw; % Change black into white and white into black.
更多回答(2 个)
Walter Roberson
2016-4-23
Foreground and background are matters of intent. For example, often binary images are white for the parts that contain the information of interest, but binary images might be representing text and text is often represented in black (corresponding to books, which use dark ink on a white page.) Chess diagrams often use both black and white for the pieces. It is therefore not possible to detect which color is the "foreground" and which color is the "background" by computer program alone.
Luis Rosety
2022-5-12
This is a very old question but I am learning Matlab and I got the same problem and just in case anybody else has the same question, I contribute with my own solution.
I realized it was quite straightforward the answer.
Assuming the input image is IM:
if(size(find(IM),1) > size(find(~IM),1))
% IM is white background
else
% IM is black background
end
1 个评论
DGM
2022-5-12
编辑:DGM
2022-5-12
Or much faster:
nz = nnz(IM);
if nz > (numel(IM)-nz)
% IM is white background
else
% IM is black background
end
You might also be able to consider the dominant value around the image periphery as some indicator of "background". I agree with Walter that the general solution requires knowledge of content and intent.
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