如何在MATLAB中测量图像的旋转？ [英] How to measure the rotation of a image in MATLAB?

问题描述

我有两张照片。一个是原版，另一个是旋转的。

I have two images. One is the original, and the another is rotated.

现在，我需要发现图像旋转的角度。到现在为止，我想到发现每种颜色的质心（因为我将使用的每个图像都有颜色的正方形），并用它来发现图像旋转了多少，但我失败了。

Now, I need to discover the angle that the image was rotated. Until now, I thought about discovering the centroids of each color (as every image I will use has squares with colors in it) and use it to discover how much the image was rotated, but I failed.

我用它来发现图像中较高方块的质心和颜色：

I'm using this to discover the centroids and the color in the higher square in the image:

i = rgb2gray(img);
bw = im2bw(i,0.01);
s = regionprops(bw,'Centroid');
centroids = cat(1, s.Centroid);
colors = impixel(img,centroids(1),centroids(2));
top = max(centroids);
topcolor = impixel(img,top(1),top(2));

推荐答案

您可以检测其中一个彩色矩形的角在图像和旋转版本中，并使用这些作为控制点来推断两个图像之间的转换（如在图像注册中）使用 CP2TFORM 功能。然后我们可以从仿射变换矩阵计算旋转角度：

You can detect the corners of one of the colored rectangles in both the image and the rotated version, and use these as control points to infer the transformation between the two images (like in image registration) using the CP2TFORM function. We can then compute the angle of rotation from the affine transformation matrix:

这是一个示例代码：

%# read first image (indexed color image)
[I1 map1] = imread('http://i.stack.imgur.com/LwuW3.png');

%# constructed rotated image
deg = -15;
I2 = imrotate(I1, deg, 'bilinear', 'crop');

%# find blue rectangle
BW1 = (I1==2);
BW2 = imrotate(BW1, deg, 'bilinear', 'crop');

%# detect corners in both
p1 = corner(BW1, 'QualityLevel',0.5);
p2 = corner(BW2, 'QualityLevel',0.5);

%# sort corners coordinates in a consistent way (counter-clockwise)
p1 = sortrows(p1,[2 1]);
p2 = sortrows(p2,[2 1]);
idx = convhull(p1(:,1), p1(:,2)); p1 = p1(idx(1:end-1),:);
idx = convhull(p2(:,1), p2(:,2)); p2 = p2(idx(1:end-1),:);

%# make sure we have the same number of corner points
sz = min(size(p1,1),size(p2,1));
p1 = p1(1:sz,:); p2 = p2(1:sz,:);

%# infer transformation from corner points
t = cp2tform(p2,p1,'nonreflective similarity');    %# 'affine'

%# rotate image to match the other
II2 = imtransform(I2, t, 'XData',[1 size(I1,2)], 'YData',[1 size(I1,1)]);

%# recover affine transformation params (translation, rotation, scale)
ss = t.tdata.Tinv(2,1);
sc = t.tdata.Tinv(1,1);
tx = t.tdata.Tinv(3,1);
ty = t.tdata.Tinv(3,2);
translation = [tx ty];
scale = sqrt(ss*ss + sc*sc);
rotation = atan2(ss,sc)*180/pi;

%# plot the results
subplot(311), imshow(I1,map1), title('I1')
hold on, plot(p1(:,1),p1(:,2),'go')
subplot(312), imshow(I2,map1), title('I2')
hold on, plot(p2(:,1),p2(:,2),'go')
subplot(313), imshow(II2,map1)
title(sprintf('recovered angle = %g',rotation))

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