Turn a 2D Image into a rotating 3D image on Matlab - image

I would like to know how to rotate a 2D image along its Z-axis using Matlab R2016b and to obtain an image after performing this procedure.
For example, let's take this 2D image:
Now, I rotate it of 45° roughly:
And now, of 90°:
Do you know if it is possible to perform the same operation in Matlab R2016b, please ?
Thank you very much for your help
Images Source: https://www.youtube.com/watch?v=m89mVexWQZ4

Yes it's possible. The easiest thing to do would be to map the image on the y = 0 plane in 3D, then rotate the camera to the desired azimuth or the angle with respect to the y axis. Once you do that, you can use the getframe / cdata idiom to actually capture the actual image data in a variable itself. The reason why you do this with respect to the y plane is because the method that I will be using to present the image is through the surf command that plots surface plots in 3D, but the y axis here is the axis that goes into and out of the screen. The x axis is the horizontal and the z axis would be the vertical when displaying data.
First read in your image using something like imread, then you need to define the 4 corners of the image that map to the 3D plane and then rotate the camera. You can use the view function to help you rotate the camera by adjusting the azimuthal angle (first parameter) and leaving the elevation angle as 0.
Something like this could work. I'll be using the peppers image that is part of the image processing toolbox:
im = imread('peppers.png'); % Read in the image
ang = 45; % Rotate clockwise by 45 degrees
% Define 4 corners of the image
X = [-0.5 0.5; -0.5 0.5];
Y = [0 0; 0 0];
Z = [0.5 0.5; -0.5 -0.5];
% Place the image on the y = 0 plane
% Turn off the axis and rotate the camera
figure;
surf(X, Y, Z, 'CData', im, 'FaceColor', 'texturemap');
axis('off');
view(ang, 0);
% Get the image data after rotation
h = getframe;
rot_im = h.cdata;
rot_im contains the rotated image. To appreciate the rotation of the image, we can loop through angles from 0 to 360 in real time. At each angle, we can use view to dynamically rotate the camera and use drawnow to update the figure. I've also updated the title of the figure to show you what the angle is at each update. The code for that is below as well as the output saved as an animated GIF:
for ang = 0 : 360
view(ang, 0);
pause(0.01);
drawnow;
title(sprintf('Angle: %d degrees', ang));
end

Related

Rotating an image matrix around its center in MATLAB

Assume I have a 2x2 matrix filled with values which will represent a plane. Now I want to rotate the plane around itself in a 3-D way, in the "z-Direction". For a better understanding, see the following image:
I wondered if this is possible by a simple affine matrix, thus I created the following simple script:
%Create a random value matrix
A = rand*ones(200,200);
%Make a box in the image
A(50:200-50,50:200-50) = 1;
Now I can apply transformations in the 2-D room simply by a rotation matrix like this:
R = affine2d([1 0 0; .5 1 0; 0 0 1])
tform = affine3d(R);
transformed = imwarp(A,tform);
However, this will not produce the desired output above, and I am not quite sure how to create the 2-D affine matrix to create such behavior.
I guess that a 3-D affine matrix can do the trick. However, if I define a 3-D affine matrix I cannot work with the 2-D representation of the matrix anymore, since MATLAB will throw the error:
The number of dimensions of the input image A must be 3 when the
specified geometric transformation is 3-D.
So how can I code the desired output with an affine matrix?
The answer from m3tho correctly addresses how you would apply the transformation you want: using fitgeotrans with a 'projective' transform, thus requiring that you specify 4 control points (i.e. 4 pairs of corresponding points in the input and output image). You can then apply this transform using imwarp.
The issue, then, is how you select these pairs of points to create your desired transformation, which in this case is to create a perspective projection. As shown below, a perspective projection takes into account that a viewing position (i.e. "camera") will have a given view angle defining a conic field of view. The scene is rendered by taking all 3-D points within this cone and projecting them onto the viewing plane, which is the plane located at the camera target which is perpendicular to the line joining the camera and its target.
Let's first assume that your image is lying in the viewing plane and that the corners are described by a normalized reference frame such that they span [-1 1] in each direction. We need to first select the degree of perspective we want by choosing a view angle and then computing the distance between the camera and the viewing plane. A view angle of around 45 degrees can mimic the sense of perspective of normal human sight, so using the corners of the viewing plane to define the edge of the conic field of view, we can compute the camera distance as follows:
camDist = sqrt(2)./tand(viewAngle./2);
Now we can use this to generate a set of control points for the transformation. We first apply a 3-D rotation to the corner points of the viewing plane, rotating around the y axis by an amount theta. This rotates them out of plane, so we now project the corner points back onto the viewing plane by defining a line from the camera through each rotated corner point and finding the point where it intersects the plane. I'm going to spare you the mathematical derivations (you can implement them yourself from the formulas in the above links), but in this case everything simplifies down to the following set of calculations:
term1 = camDist.*cosd(theta);
term2 = camDist-sind(theta);
term3 = camDist+sind(theta);
outP = [-term1./term2 camDist./term2; ...
term1./term3 camDist./term3; ...
term1./term3 -camDist./term3; ...
-term1./term2 -camDist./term2];
And outP now contains your normalized set of control points in the output image. Given an image of size s, we can create a set of input and output control points as follows:
scaledInP = [1 s(1); s(2) s(1); s(2) 1; 1 1];
scaledOutP = bsxfun(#times, outP+1, s([2 1])-1)./2+1;
And you can apply the transformation like so:
tform = fitgeotrans(scaledInP, scaledOutP, 'projective');
outputView = imref2d(s);
newImage = imwarp(oldImage, tform, 'OutputView', outputView);
The only issue you may come across is that a rotation of 90 degrees (i.e. looking end-on at the image plane) would create a set of collinear points that would cause fitgeotrans to error out. In such a case, you would technically just want a blank image, because you can't see a 2-D object when looking at it edge-on.
Here's some code illustrating the above transformations by animating a spinning image:
img = imread('peppers.png');
s = size(img);
outputView = imref2d(s);
scaledInP = [1 s(1); s(2) s(1); s(2) 1; 1 1];
viewAngle = 45;
camDist = sqrt(2)./tand(viewAngle./2);
for theta = linspace(0, 360, 360)
term1 = camDist.*cosd(theta);
term2 = camDist-sind(theta);
term3 = camDist+sind(theta);
outP = [-term1./term2 camDist./term2; ...
term1./term3 camDist./term3; ...
term1./term3 -camDist./term3; ...
-term1./term2 -camDist./term2];
scaledOutP = bsxfun(#times, outP+1, s([2 1])-1)./2+1;
tform = fitgeotrans(scaledInP, scaledOutP, 'projective');
spinImage = imwarp(img, tform, 'OutputView', outputView);
if (theta == 0)
hImage = image(spinImage);
set(gca, 'Visible', 'off');
else
set(hImage, 'CData', spinImage);
end
drawnow;
end
And here's the animation:
You can perform a projective transformation that can be estimated using the position of the corners in the first and second image.
originalP='peppers.png';
original = imread(originalP);
imshow(original);
s = size(original);
matchedPoints1 = [1 1;1 s(1);s(2) s(1);s(2) 1];
matchedPoints2 = [1 1;1 s(1);s(2) s(1)-100;s(2) 100];
transformType = 'projective';
tform = fitgeotrans(matchedPoints1,matchedPoints2,'projective');
outputView = imref2d(size(original));
Ir = imwarp(original,tform,'OutputView',outputView);
figure; imshow(Ir);
This is the result of the code above:
Original image:
Transformed image:

Changing the centre of transformation/mapping in polar coordinate MATLAB

After applying the following code I get output mapped image started from centre top point. How can I put the starting point to left bottom corner? So, the output image should be stretched from left bottom point(not from top centre as it is now)...
im = imread ('peppers.png');
im = rgb2gray(im);
[nZ,nX] = size(im);
theta = ((0:(nX-1))-nX/2)*(0.1*(pi/180)) - pi/2;
rr = (0:(nZ-1))*0.1e-3;
%% Plot image in rectangular coordinates
figure
imagesc(theta*(180/pi), rr*1e3, im)
xlabel('theta [deg]')
ylabel('r [mm]')
%% Create grids and convert polar coordinates to rectangular
[THETA,RR] = meshgrid(theta,rr);
[XX,YY] = pol2cart(THETA,RR);
%% Plot as surface, viewed from above
figure
surf(XX*1e3,YY*1e3,im,'edgecolor','none')
view(0,90)
xlabel('x [mm]')
ylabel('y [mm]')

MATLAB How to convert axis coordinates to pixel coordinates?

What is the preferred way of converting from axis coordinates (e.g. those taken in by plot or those output in point1 and point2 of houghlines) to pixel coordinates in an image?
I see the function axes2pix in the Mathworks documentation, but it is unclear how it works. Specifically, what is the third argument? The examples just pass in 30, but it is unclear where this value comes from. The explanations depend on a knowledge of several other functions, which I don't know.
The related question: Axis coordinates to pixel coordinates? suggests using poly2mask, which would work for a polygon, but how do I do the same thing for a single point, or a list of points?
That question also links to Scripts to Convert Image to and from Graph Coordinates, but that code threw an exception:
Error using /
Matrix dimensions must agree.
Consider the following code. It shows how to convert from axes coordinates to image pixel coordinates.
This is especially useful if you plot the image using custom XData/YData locations other than the default 1:width and 1:height. I am shifting by 100 and 200 pixels in the x/y directions in the example below.
function imageExample()
%# RGB image
img = imread('peppers.png');
sz = size(img);
%# show image
hFig = figure();
hAx = axes();
image([1 sz(2)]+100, [1 sz(1)]+200, img) %# shifted XData/YData
%# hook-up mouse button-down event
set(hFig, 'WindowButtonDownFcn',#mouseDown)
function mouseDown(o,e)
%# get current point
p = get(hAx,'CurrentPoint');
p = p(1,1:2);
%# convert axes coordinates to image pixel coordinates
%# I am also rounding to integers
x = round( axes2pix(sz(2), [1 sz(2)], p(1)) );
y = round( axes2pix(sz(1), [1 sz(1)], p(2)) );
%# show (x,y) pixel in title
title( sprintf('image pixel = (%d,%d)',x,y) )
end
end
(note how the axis limits do not start at (1,1), thus the need for axes2pix)
There may be a built-in way that I haven't heard of, but this shouldn't be hard to do from scratch...
set(axes_handle,'units','pixels');
pos = get(axes_handle,'position');
xlim = get(axes_handle,'xlim');
ylim = get(axes_handle,'ylim');
Using these values, you can convert from axes coordinates to pixels easily.
x_in_pixels = pos(1) + pos(3) * (x_in_axes-xlim(1))/(xlim(2)-xlim(1));
%# etc...
The above uses pos(1) as the x-offset of the axes within the figure. If you don't care about this, don't use it. Likewise, if you want it in screen coordinates, add the x-offset of the position obtained by get(figure_handle,'position')

How to lock image dimensions in MATLAB

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;

How can I plot an image (.jpg) in MATLAB in both 2-D and 3-D?

I have a 2-D scatter plot and at the origin I want to display an image (not a colorful square, but an actual picture). Is there any way to do this?
I also will be plotting a 3-D sphere in which I would like an image to be displayed at the origin as well.
For 2-D plots...
The function IMAGE is what you're looking for. Here's an example:
img = imread('peppers.png'); %# Load a sample image
scatter(rand(1,20)-0.5,rand(1,20)-0.5); %# Plot some random data
hold on; %# Add to the plot
image([-0.1 0.1],[0.1 -0.1],img); %# Plot the image
For 3-D plots...
The IMAGE function is no longer appropriate, as the image will not be displayed unless the axis is viewed from directly above (i.e. from along the positive z-axis). In this case you will have to create a surface in 3-D using the SURF function and texture map the image onto it. Here's an example:
[xSphere,ySphere,zSphere] = sphere(16); %# Points on a sphere
scatter3(xSphere(:),ySphere(:),zSphere(:),'.'); %# Plot the points
axis equal; %# Make the axes scales match
hold on; %# Add to the plot
xlabel('x');
ylabel('y');
zlabel('z');
img = imread('peppers.png'); %# Load a sample image
xImage = [-0.5 0.5; -0.5 0.5]; %# The x data for the image corners
yImage = [0 0; 0 0]; %# The y data for the image corners
zImage = [0.5 0.5; -0.5 -0.5]; %# The z data for the image corners
surf(xImage,yImage,zImage,... %# Plot the surface
'CData',img,...
'FaceColor','texturemap');
Note that this surface is fixed in space, so the image will not always be directly facing the camera as you rotate the axes. If you want the texture-mapped surface to automatically rotate so that it is always perpendicular to the line of sight of the camera, it's a much more involved process.

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