I've got a picture (a matrix of intensities for every pixel). When plotting this with matlab's imagesc the x-,y-axis are obviously in pixels. I know that 1 pixel corresponds to 0.6250 millimeter in both x- and y-direction.
How can I change only the scale in axis in the figure to show millimeters instead of pixels, i.e how do I multiply the xticks and yticks with 0.6250 and have it displayed in the figure?
I have tried:
new_x = xticks*pixel_spacing(2);
set(gca,'xticklabels', new_x)
but this results in the error
"Unable to use a value of type 'matlab.graphics.axis.Axes' as an index."
imagesc has a syntax where you can specify the scaling of the pixels (see the documentation).
x = [1,size(img,2)] * pixel_spacing;
y = [1,size(img,1)] * pixel_spacing;
imagesc(x,y,img);
(assuming img is your image to display)
The advantage over changing the tick labels is that other things plotted on top of the image will use the same coordinates, as will retrieving mouse cursor location and so forth. This might or might not be relevant, but it’s good to know.
I figured it out.
xticklabels(xticks*pixel_spacing(2))
yticklabels(yticks*pixel_spacing(1))
Related
So I have this matrix in MATLAB, 200 deep x 600 wide. It represents an image that is 2cm deep x 6cm wide. How can I plot this image so that it is locked into proper dimensions, i.e. 2cm x 6cm? If I use the image or imagesc commands it stretches it all out of shape and shows it the wrong size. Is there a way to lock it into showing an image where the x and y axes are proportional?
Second question, I need to then set this image into a 640x480 frame (20 pixel black margin on left and right, 280 pixel black margin on bottom). Is there a way to do this?
To keep aspect ratio, you can use axis equal or axis image commands.
Quoting the documentation:
axis equal sets the aspect ratio so that the data units are the same in every direction. The aspect ratio of the x-, y-, and z-axis is adjusted automatically according to the range of data units in the x, y, and z directions.
axis image is the same as axis equal except that the plot box fits tightly around the data`
For second question:
third_dimension_size=1; %# for b&w images, use 3 for rgb
framed_image=squeeze(zeros(640,480,third_dimension_size));
framed_image(20:20+600-1,140:140+200-1)= my_600_200_image;
imagesc(framed_image'); axis image;
set(gca,'DataAspectRatio',[1 1 1])
Second question:
new_image = zeros(480,640);
new_image(20:(200+20-1),20:(600+20-1)) = old_image;
As an alternative to the other answers, you might want:
set(gca, 'Units', 'centimeters', 'Position', [1 1 6 2])
Make sure you do this after plotting the image to get the other axis properties correct.
For the second question, take care with the number of colour channels:
new_image = zeros(480,640, size(old_image));
new_image(20:(200+20-1),20:(600+20-1),:) = old_image;
I'm using regionprops(img,'BoundingBox'); to generate bounding boxes around some objects in an image. The coordinates of the bounding boxes (x, y, width, height) are always by 0.5 off from Integer-values.
Why is that the case?
For me, it is causing two problems:
When using these coordinates for accessing an image array, I get the warning: Warning: Integer operands are required for colon operator when used as index. I can live with that, respectively remove it with floor or ceil, BUT ...
... when these coordinates are close to image borders, they cause
errors since the values 0.5 and 1024.5 don't match with the image
borders 1 and 1024. I get Subscripted assignment dimension mismatch. or Index exceed matrix dimensions., which is plausible.
So can someone explain to me:
Why is it doing this?
How am I supposed to work with it when using the coordinates to crop and replace image regions. I want to replace exactly what was cropped by imcrop and rounding is a bit circumstancial (simply using floor or ceil won't work, I would have to check for the image borders which is not a problem but seems a bit tedious for a rather simple task and certainly questionable whether it is supposed to be used like this...).
Below are some code snippets with which I produced the errors for a 1024x1024 image.
bb_coords = [124.5 979.5 27 45]; % example for bounding box generated by regionprops
subregion = imcrop(img, bb_coords); % works fine with imcrop
% but when I want to use these coordinates for accessing the img array,
% I generally get a warning and in this case an error.
img( bb_coords(2):(bb_coords(2)+bb_coords(4)), ...
bb_coords(1):(bb_coords(1)+bb_coords(3))) = subregion;
Functions in MATLAB that handle image display or processing treat the center of the pixel as lining up with the corresponding coordinate grid points. In other words, for a given dimension of an image, the first pixel center is at 1, the second pixel center is at 2, etc., and the area of each pixel will span +-0.5 on either side of the coordinate. You can see this when you plot an image, turn the axes display on, and zoom in around one of the corners:
img = imread('cameraman.tif'); % Load a sample image
imshow(img); % Display it
set(gca, 'Visible', 'on'); % Make the axes visible
axis([0 5 252 257]); % Zoom in on the bottom left corner
The documentation for regionprops illustrates that the 'BoundingBox' will enclose the entire pixel area, thus leading to a bounding box that appears a full pixel wider (0.5 pixels wider on each side) than the range of center coordinates:
For the 5-by-5 sample image above, the nonzero pixels cover an area that spans the top 4 rows (row coordinates of the pixel centers from 1 to 4) and right 4 columns (column coordinates of the pixel centers from 2 to 5). The bounding box (in green) therefore spans from 0.5 to 4.5 (height of 4) across the rows and 1.5 to 5.5 (width of 4) across the columns.
In short, if you want to use the bounding box values in bb_coords to generate indices into the image, you need to add 0.5 to each corner coordinate and subtract 1 from each width:
ind_coords = bb_coords + [0.5 0.5 -1 -1];
img(ind_coords(2):(ind_coords(2)+ind_coords(4)), ...
ind_coords(1):(ind_coords(1)+ind_coords(3))) = subregion;
I have written a program to process and print a 81x81 2D surface plot, which needs to be used as an input. Saving the plot made by Matlab includes side axes as well as white margins on the sides.
How do I crop this image to get just the (81pixels)x(81pixels) output as an image?
Try placing this after your figure code, it will remove the margins around your figure.
set(gca,'units','pixels') % set the axes units to pixels
xx = get(gca,'position'); % get the position of the axes;
set(gcf,'units','pixels') % set the figure units to pixels
yy = get(gcf,'position'); % get the figure position;
set(gcf,'position',[yy(1) yy(2) xx(3) xx(4)]) % set the position of the figure to the length and width of the axes
set(gca,'units','normalized','position',[0 0 1 1]) % set the axes units to pixels
You can avoid using surf plot and just save your array as image. So, you have 81x81 array. I'll use this one for the example:
a = magic(81);
Now you need to normalize image in order to have values from 0 to 255:
a = (a - min(min(a)))/(max(max(a))-min(min(a)))*255;
Finally you use imwrite to save your array as image.
imwrite(a,jet(256),'SO_4.png')
The first argument is your 81x81 array. The second argument is colormap. You can specify any colormap you want, but I like the heatmap jet(256). You can skip this argument, in this case the image would be grayscale. From here you can find what colormaps are available and what they look like. The last argument is image name. The result is shown below:
Hope that helps, good luck.
I want to detect edges (with sub-pixel accuracy) in images like the one displayed:
The resolution would be around 600 X 1000.
I came across a comment by Mark Ransom here, which mentions about edge detection algorithms for vertical edges. I haven't come across any yet. Will it be useful in my case (since the edge isn't strictly a straight line)? It will always be a vertical edge though. I want it to be accurate till 1/100th of a pixel at least. I also want to have access to these sub-pixel co-ordinate values.
I have tried "Accurate subpixel edge location" by Agustin Trujillo-Pino. But this does not give me a continuous edge.
Are there any other algorithms available? I will be using MATLAB for this.
I have attached another similar image which the algorithm has to work on:
Any inputs will be appreciated.
Thank you.
Edit:
I was wondering if I could do this:
Apply Canny / Sobel in MATLAB and get the edges of this image (note that it won't be a continuous line). Then, somehow interpolate this Sobel edges and get the co-ordinates in subpixel. Is it possible?
A simple approach would be to project your image vertically and fit the projected profile with an appropriate function.
Here is a try, with an atan shape:
% Load image
Img = double(imread('bQsu5.png'));
% Project
x = 1:size(Img,2);
y = mean(Img,1);
% Fit
f = fit(x', y', 'a+b*atan((x0-x)/w)', 'Startpoint', [150 50 10 150])
% Display
figure
hold on
plot(x, y);
plot(f);
legend('Projected profile', 'atan fit');
And the result:
I get x_0 = 149.6 pix for your first image.
However, I doubt you will be able to achieve a subpixel accuracy of 1/100th of pixel with those images, for several reasons:
As you can see on the profile, your whites are saturated (grey levels at 255). As you cut the real atan profile, the fit is biased. If you have control over the experiments, I suggest you do it again again with a smaller exposure time for instance.
There are not so many points on the transition, so there is not so many information on where the transition is. Typically, your resolution will be the square root of the width of the atan (or whatever shape you prefer). In you case this limits the subpixel resolution at 1/5th of a pixel, at best.
Finally, your edges are not stricly vertical, they are slightly titled. If you choose to use this projection method, to increase the accuracy you should look for a way to correct this tilt before projecting. This won't increase your accuracy by several orders of magnitude, though.
Best,
There is a problem with your image. At pixel level, it seems like there are four interlaced subimages (odd and even rows and columns). Look at this zoomed area close to the edge.
In order to avoid this artifact, I just have taken the even rows and columns of your image, and compute subpixel edges. And finally, I look for the best fitting straight line, using the function clsq whose code is in this page:
%load image
url='http://i.stack.imgur.com/bQsu5.png';
image = imread(url);
imageEvenEven = image(1:2:end,1:2:end);
imshow(imageEvenEven, 'InitialMagnification', 'fit');
% subpixel detection
threshold = 25;
edges = subpixelEdges(imageEvenEven, threshold);
visEdges(edges);
% compute fit line
A = [ones(size(edges.x)) edges.x edges.y];
[c n] = clsq(A,2);
y = [1,200];
x = -(n(2)*y+c) / n(1);
hold on;
plot(x,y,'g');
When executing this code, you can see the green line that best aproximate all the edge points. The line is given by the equation c + n(1)*x + n(2)*y = 0
Take into account that this image has been scaled by 1/2 when taking only even rows and columns, so the right coordinates must be scaled.
Besides, you can try with the other tree subimages (imageEvenOdd, imageOddEven and imageOddOdd) and combine the four straigh lines to obtain the best solution.
I am trying to plot a matrix where each element is in one out of two states. (ising model..)
Now, I would like to have one state colored and the other one white. That works using
[i,j] = find(S);
figure(gcf);
plothandle = scatter(i,j);
axis([0 nNodes+1 0 nNodes+1]);
when S holds the Spins and one state is equal to 0. (find returns a matrix of only non-zero elements)
To have a useful plot, the sizes of the markers should be 1x1 in RELATIVE coordinates. So if the whole matrix S would be in a state non-zero, everything would be colored.
However, it seems like Matlab only allows MarkerSizes in points or inches. How could I solve this?
One idea I had was, that I find out the point-size of the axes and then can easily calculate how big my markers should be. Then I would have to create a callback function if I want to zoom in and so on. Also, I have not yet found a way (without the image acq. toolbox) to find out the absolute size of my axes.
To clarify what I want: How could I plot a chessboard using a matrix with 1 for black and 0 for white fields?
For displaying data of this sort I generally prefer IMAGE or IMAGESC to PCOLOR since PCOLOR won't display the last row and column of the matrix when using faceted shading (the default). Also, IMAGE and IMAGESC flip the y axis so the image more intuitively matches what you think of when looking at a matrix (i.e. rows start from 1 at the top). You can visualize your matrix like this:
S = round(rand(20)); %# Sample 20-by-20 matrix of ones and zeroes
imagesc(S); %# Plot the image
colormap([1 1 1; 0 0 0]); %# Set the colormap to show white (zero elements) and
%# black (non-zero elements)
And here's a sample image:
Just as a suggestion, you can try using pcolor instead of `scatter' Example:
pcolor(hadamard(20))
colormap(gray(2))
axis ij
axis square