eg I want to find the color values of the center of this image
how can i do this?
you mean
img = imread('img.jpg');
color = img(round(end/2), round(end/2), :)
?
Related
I want to segment my grayscale image as following:
img = io.imread(curr_img_path)
gray = color.rgb2gray(img)
assignment1 = slic(image=gray, n_segments=500, sigma=2, max_iter=100)
I am looking at the segmented image using
fig, ax = plt.subplots(2, 2, figsize=(10, 10), sharex=True, sharey=True)
ax[0, 0].imshow(mark_boundaries(gray, assignment1))
plt.show()
My problem: This shows me a normal grid. Like a chessboard. I do not understand why, and the docs say its possible using grayscale images. Any help? Btw: My image is of shape (352,1216), dtype= float64. There is no error message or something else. Would be glad for any help.
While the compactness parameter can be left to the default value for image in lab-space, the default parameter is to high for RGB/Grayscale images.
I have an image like this:
my goal is to get the output under background normalization at this link.
Following the above link, I did the following:
(1). I first dilate the image to get the background
(2). then try to remove it via normalization
I got the background:
However, when I try to do the normalized division, I get this :
(black borders added to make clear of the boundary of the image)
this is my code:
image = imread('image.png');
image = rgb2gray(image);
se = offsetstrel('ball',9,9);
dilatedI = imdilate(image,se);
output = imdivide(image,dilatedI);
imshow(output,[]);
using
imshow(output)
just gives a black image.
I thought it might be a type conversion issue, but based on the resources mentioned earlier, I am uncertain if it is the case...
Any advice would be appreciated
Just make sure you dont do integer division! your images are integer type, so 4/5 returns 0 and 5/4 returns 1, not a floating point number. Just convert to float before dividing:
image = imread('https://i.stack.imgur.com/bIVRT.png');
%image = rgb2gray(image); The image is not a RGB online
se = offsetstrel('ball',21,21);
dilatedI = imdilate(image,se);
output = imdivide(double(image),double(dilatedI));
figure
subplot(121)
imshow(image);
subplot(122)
imshow(output);
I am struggling with some algorithm to extract the region from an image which has the maximum change in pixels. I got the following image after preprocessing.
I did following steps of pre-processing
x = imread('test2.jpg');
gray_x = rgb2gray(x);
I = medfilt2(gray_x,[3 3]);
gray_x = I;
%%
canny_x = edge(gray_x,'canny',0.3);
figure,imshow(canny_x);
%%
s = strel('disk',3);
si = imdilate(canny_x,s);
%figure5
figure; imshow(si);
se = imerode(canny_x,s);title('dilation');
%figure6
figure; imshow(se);title('Erodsion');
I = imsubtract(si,se);
%figure7
figure; imshow(I);
Basically what I am struggling for, is to make weapon detection system using Image processing. I want to localize possible area's to be weapon so that I could feed them to my classifier to identify if it is a weapon or not. Any suggestions? Thank you
A possible solution could be:
Find corner points in the image (Harris corner points, etc)
Set value of all the corner points to white while remaining image will be black
Take a rectangular window and traverse it over the whole image
sum all the white pixels in that rectangular window
select that region whose sum is maximum of all regions
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
This is my code. The output is not exactly gray. Can someone tell me what is the problem in the code ?
obj = VideoReader('shaky_cars.avi');
height = obj.Height;
width = obj.Width;
factor = 200/height;
num=10;
intendedFrame = 20;
video = read(obj , [intendedFrame , intendedFrame+num]);
for i = 1:1+num
grayVideo(:,:,i) = double(imresize((rgb2gray(video(:,:,:,i))) , factor));
end
[height , width] = size(grayVideo(:,:,1));
figure(1);imagesc(grayVideo(:,:,1));
And this is the output
A few questions: Have you printed out the images before and after to see what's happening at each step?
Why are you converting the frames to type double?
Suggestion: Try converting the image to uint8 by doing uint8(grayVideo(:,:,i)) and use a gray colormap colormap(gray(256)).
Let me know if this helps
Instead of using imagesc, you can use
imshow(uint8(grayVideo(:,:,1)))
to display your grayscale images.