the figure outputted just displays the binary mask image, however I am trying to get just the foreground of the coloured image, with the background being black.
original = imread('originalImage.jpg');
binaryImage = imread('binaryImage.png');
mask = cat(3,binaryImage, binaryImage, binaryImage);
output = mask.*original;
figure,imshow(output);
the binary mask
The original image
The most likely issue is that binary is an image with values of 0 for background and 255 for foreground. Multiplying a color image with values in the range [0,255] by such a mask leads to overflow. Since the input images are uint8, overflow leads to values of 255. Thus, everywhere where the mask is white, you get white colors.
The solution is to convert the images to double:
output = double(mask)/255 .* double(original)/255;
or to truly binarize the mask image:
output = (mask>0) .* original;
Related
I have a RGB image that I have processed and binarized and now I would like to return the original color only for the regions that now are white on the binarized image.
Is it possible to do so?
I've tried doing the following code, first I convert the data type from logical to double and then I try to return the original color, but it seems that doesn't works. The resulting image is a completely white image.
rz = double(rz);
rz(:,:,3)=I2(:,:,3);
rz(:,:,2)=I2(:,:,2);
rz(:,:,1)=I2(:,:,1);
rz is the binarized image while I2 is the original RGB image.
Is it possible to return the original color only for the regions that are white on the binarized image? What I'm doing wrong?
Assuming rz is logical NxMx1 image (i.e. you did not binarize differently in each dimensions)
Iout=I2;
Iout=bsxfun(#times,Iout,uint8(rz))
does the job. Basically you convert rz to double, and then multiply it with each color channel of Iout (using bsxfun). The resulting image will have the color [0,0,0] if the mask is zero in that pixel.
I have 2 images. One is background image and other image has same background but with some foreground object. I want to extract foreground object from background. Simple subtraction operation in matlab will not suffice as it subtracts RGB value of background image from that of foreground image (as in below code).
im1 = imread('output/frame-1.jpg')
im2 = imread('output/frame-7.jpg')
%# subtract
deltaImage = im1 - im2;
imshow(deltaImage)
So if background color is white and foreground object is blue, then output (i.e. deltaImage) comes foreground object with orange color with black background. However the output I want is foreground object with blue color (i.e. original color) with black background. How can I get this ? I tried to do it using below code, but output image is incorrect.
im1 = imread('foreground.jpg')
im2 = imread('background.jpg')
[m n k]=size(im2);
deltaImage = zeros(m,n,3);
fprintf('%d %d %d.\n',m,n,k);
for l=1:k
for i=1:m-1
for j=1:n-1
if im1(i:j:l)~=im2(i:j:l)
deltaImage(i,j,l) = im1(i,j,l);
end
end
end
end
imshow(deltaImage)
Background IMAGE
Foreground Image
Output Image (Here I want color of man to be blue)
You can use deltaImage to create a mask (zeros and ones image) that multiplies the foreground. However, note that you will have artifacts associated with lossy image compression (.jpeg). These can be reduced, to some extent, if you use a threshold, like the average difference or a specific value you want. Try this:
im1 = double(imread('~/Downloads/foreground.jpg'));
im2 = double(imread('~/Downloads/background.jpg'));
compute the difference of the averages of the 3 channels
deltaImage = mean(im2,3) - mean(im1,3);
then use the product of the mean by a standard deviation (~3), or uncomment the line below to use a specific threshold, like 128
mask = deltaImage>3*mean(deltaImage(:));
% mask = deltaImage>128;
then assuming all original images are in 8-bit format produce a result also in 8-bit format:
result = uint8(cat(3, im1(:,:,1).*mask, im1(:,:,2).*mask, im1(:,:,3).*mask));
imshow(result)
And this is the result you should get:
Again the weird looking pixels around the main object are artifacts of lossy image compression (.jpeg), you should try working with lossless like .png formats.
I have an image and a subimage which is cropped out of the original image.
Here's the code I have written so far:
val1 = imread(img);
val2 = imread(img_w);
gray1 = rgb2gray(val1);%grayscaling both images
gray2 = rgb2gray(val2);
matchingval = normxcorr2(gray1,gray2);%normalized cross correlation
[max_c,imax]=max(abs(matchingval(:)));
After this I am stuck. I have no idea how to change the whole image grayscale except for the sub image which should be in color.
How do I do this?
Thank you.
If you know what the coordinates are for your image, you can always just use the rgb2gray on just the section of interest.
For instance, I tried this on an image just now:
im(500:1045,500:1200,1)=rgb2gray(im(500:1045,500:1200,1:3));
im(500:1045,500:1200,2)=rgb2gray(im(500:1045,500:1200,1:3));
im(500:1045,500:1200,3)=rgb2gray(im(500:1045,500:1200,1:3));
Where I took the rows (500 to 1045), columns (500 to 1200), and the rgb depth (1 to 3) of the image and applied the rgb2gray function to just that. I did it three times as the output of rgb2gray is a 2d matrix and a color image is a 3d matrix, so I needed to change it layer by layer.
This worked for me, making only part of the image gray but leaving the rest in color.
The issue you might have though is this, a color image is 3 dimensions while a gray scale need only be 2 dimensions. Combining them means that the gray scale must be in a 3d matrix.
Depending on what you want to do, this technique may or may not help.
Judging from your code, you are reading the image and the subimage in MATLAB. What you need to know are the coordinates of where you extracted the subimage. Once you do that, simply take your original colour image, convert that to grayscale, then duplicate this image in the third dimension three times. You need to do this so that you can place colour pixels in this image.
For RGB images, grayscale images have the RGB components to all be the same. Duplicating this image in the third dimension three times creates the RGB version of the grayscale image. Once you do that, simply use the row and column coordinates of where you extracted the subimage and place that into the equivalent RGB grayscale image.
As such, given your colour image that is stored in img and your subimage stored in imgsub, and specifying the rows and columns of where you extracted the subimage in row1,col1 and row2,col2 - with row1,col1 being the top left corner of the subimage and row2,col2 is the bottom right corner, do this:
img_gray = rgb2gray(img);
img_gray = cat(3, img_gray, img_gray, img_gray);
img_gray(row1:row2, col1:col2,:) = imgsub;
To demonstrate this, let's try this with an image in MATLAB. We'll use the onion.png image that's part of the image processing toolbox in MATLAB. Therefore:
img = imread('onion.png');
Let's also define our row1,col1,row2,col2:
row1 = 50;
row2 = 90;
col1 = 80;
col2 = 150;
Let's get the subimage:
imgsub = img(row1:row2,col1:col2,:);
Running the above code, this is the image we get:
I took the same example as rayryeng's answer and tried to solve by HSV conversion.
The basic idea is to set the second layer i.e saturation layer to 0 (so that they are grayscale). then rewrite the layer with the original saturation layer only for the sub image area, so that, they alone have the saturation values.
Code:
img = imread('onion.png');
img = rgb2hsv(img);
sPlane = zeros(size(img(:,:,1)));
sPlane(50:90,80:150) = img(50:90,80:150,2);
img(:,:,2) = sPlane;
img = hsv2rgb(img);
imshow(img);
Output: (Same as rayryeng's output)
Related Answer with more details here
I have a retinal fundus image which has a white border along the corners. I am trying to remove the borders on all four sides of the image. This is a pre-processing step and my image looks like this:
fundus http://snag.gy/XLGkC.jpg
It is an RGB image, and I took the green channel, and created a mask using logical indexing. I searched for pixels which were all black in the image, and eroded the mask to remove the white edge pixels. However, I am not sure how to retrieve the final image, without the white pixel border using the mask that I have. This is my code, and any help would be appreciated:
maskIdx = rgb(:,:,2) == 0; # rgb is the original image
se = strel('disk',3); # erode 3-pixel using a disk structuring element
im2 = imerode(maskIdx, se);
newrgb = rgb(im2); # gives a vector - not the same size as original im
Solved it myself. This is what I did with some help.
I first computed the mask for all three color channels combined. This is because the mask for each channel is not the same when applied to all the three channels individually, and residual pixels will be left in the final image if I used only the mask from one of the channels in the original image:
mask = (rgb(:,:,1) == 0) & (rgb(:,:,2) == 0) & (rgb(:,:,3) == 0);
Next, I used a disk structuring element with a radius of 9 pixels to dilate my mask:
se = strel('disk', 9);
maskIdx = imdilate(mask,se);
EDIT: A structuring element which is arbitrary can also be used. I used: se = strel(ones(9,9))
Then, with the new mask, I multiplied the original image with the new dilated mask:
newImg(:,:,1) = rgb(:,:,1) .* uint8(maskIdx); # image was of double data-type
newImg(:,:,2) = rgb(:,:,2) .* uint8(maskIdx);
newImg(:,:,3) = rgb(:,:,3) .* uint8(maskIdx);
Finally, I subtracted the computed color-mask from the original image to get my desired border-removed image:
finalImg = rgb - newImg;
Result:
image http://snag.gy/g2X1v.jpg
I have imported an image in matlab and before I display it how would I make the background of the image transparent? For example I have a red ball on a white background, how would i make the white pixels of the image tranparent so that only the red ball is visible and the white pixels are transparent?
You need to make sure the image is saved in the 'png' format. Then you can use the 'Alpha' parameter of a png file, which is a matrix that specifies the transparency of each pixel individually. It is essentially a boolean matrix that is 1 if the pixel is transparent, and 0 if not. This can be done easily with a for loop as long as the color that you want to be transparent is always the same value (i.e. 255 for uint8). If it is not always the same value then you could define a threshold, or range of values, where that pixel would be transparent.
Update :
First generate the alpha matrix by iterating through the image and (assuming you set white to be transparent) whenever the pixel is white, set the alpha matrix at that pixel as 1.
# X is your image
[M,N] = size(X);
# Assign A as zero
A = zeros(M,N);
# Iterate through X, to assign A
for i=1:M
for j=1:N
if(X(i,j) == 255) # Assuming uint8, 255 would be white
A(i,j) = 1; # Assign 1 to transparent color(white)
end
end
end
Then use this newly created alpha matrix (A) to save the image as a ".png"
imwrite(X,'your_image.png','Alpha',A);
Note for loops in MATLAB should be avoided at all costs because they are slow. Rewriting code to remove the loops is commonly referred to as "vectorizing" code. In the case of ademing2's answer, it could be done as follows:
A = zeros(size(X));
A(X == 255) = 1;