affine2d

2-D affine geometric transformation

Description

An affine2d object stores information about a 2-D affine geometric transformation and enables forward and inverse transformations.

Creation

You can create an affine2d object in these ways:

• imregtform — Estimate a geometric transformation that maps a moving image to a fixed image using similarity optimization.

• imregcorr — Estimate a geometric transformation that maps a moving image to a fixed image using phase correlation.

• fitgeotrans — Estimate a geometric transformation that maps pairs of control points between two images.

• randomAffine2d — Create a randomized 2-D affine transformation.

• The affine2d function described here.

Syntax

tform = affine2d

tform = affine2d(T)

Description

tform = affine2d creates an affine2d object with default property settings that correspond to the identity transformation.

tform = affine2d(T) sets the property T as the specified valid affine transformation matrix.

Properties

T — Forward 2-D affine transformation

nonsingular 3-by-3 numeric matrix

Forward 2-D affine transformation, specified as a nonsingular 3-by-3 numeric matrix.

The matrix T uses the convention:

[x y 1] = [u v 1] * T

where T has the form:

 [a b 0;
  c d 0;
  e f 1];

The default of T is the identity transformation.

Data Types: double | single

Dimensionality — Dimensionality of geometric transformation

2

Dimensionality of the geometric transformation for both input and output points, specified as the value 2.

Object Functions

invert	Invert geometric transformation
isRigid	Determine if transformation is rigid transformation
isSimilarity	Determine if transformation is similarity transformation
isTranslation	Determine if transformation is pure translation
outputLimits	Find output spatial limits given input spatial limits
transformPointsForward	Apply forward geometric transformation
transformPointsInverse	Apply inverse geometric transformation

Examples

Define 2-D Affine Transformation from Transformation Matrix

Create an affine2d object that defines a 30 degree rotation in the counterclockwise direction around the origin.

theta = 30;
tform = affine2d([ ...
    cosd(theta) sind(theta) 0;...
    -sind(theta) cosd(theta) 0; ...
    0 0 1])

tform = 
  affine2d with properties:

                 T: [3x3 double]
    Dimensionality: 2

Apply the forward geometric transformation to a point (10,0).

[x,y] = transformPointsForward(tform,10,0)

x = 8.6603

y = 5

Validate the transformation by plotting the original point (in blue) and the transformed point (in red).

plot(10,0,'bo',x,y,'ro')
axis([0 12 0 12])
axis square

Transform Image Using 2-D Affine Transformation Object

Read an image into the workspace.

A = imread('pout.tif');

Create an affine2d object that defines an affine geometric transformation. This example combines vertical shear and horizontal stretch.

tform = affine2d([2 0.33 0; 0 1 0; 0 0 1])

tform = 
  affine2d with properties:

                 T: [3x3 double]
    Dimensionality: 2

Apply the geometric transformation to the image using imwarp.

B = imwarp(A,tform);

Display the resulting image.

figure
imshow(B);
axis on equal;

Randomly Rotate Image

Read and display an image.

I = imread('kobi.png');
imshow(I)

Create an affine2d transformation object that rotates images. The randomAffine2d function picks a rotation angle randomly from a continuous uniform distribution within the interval [35, 55] degrees.

tform1 = randomAffine2d('Rotation',[35 55]);

Rotate the image and display the result.

J = imwarp(I,tform1);
imshow(J)

The transformation object, tform1, rotates all images by the same amount. To rotate an image by a different randomly selected amount, create a new affine2d transformation object.

tform2 = randomAffine2d('Rotation',[-10 10]);
J2 = imwarp(I,tform2);
imshow(J2)

Create Geometric Transformation for Image Alignment

This example shows how to create a geometric transformation that can be used to align two images.

Create a checkerboard image and rotate it to create a misaligned image.

I = checkerboard(40);
J = imrotate(I,30);
imshowpair(I,J,'montage')

Define some matching control points on the fixed image (the checkerboard) and moving image (the rotated checkerboard). You can define points interactively using the Control Point Selection tool.

fixedPoints = [41 41; 281 161];
movingPoints = [56 175; 324 160];

Create a geometric transformation that can be used to align the two images, returned as an affine2d geometric transformation object.

tform = fitgeotrans(movingPoints,fixedPoints,'NonreflectiveSimilarity')

tform = 
  affine2d with properties:

                 T: [3x3 double]
    Dimensionality: 2

Use the tform estimate to resample the rotated image to register it with the fixed image. The regions of color (green and magenta) in the false color overlay image indicate error in the registration. This error comes from a lack of precise correspondence in the control points.

Jregistered = imwarp(J,tform,'OutputView',imref2d(size(I)));
figure
imshowpair(I,Jregistered)

Recover angle and scale of the transformation by checking how a unit vector parallel to the x-axis is rotated and stretched.

u = [0 1]; 
v = [0 0]; 
[x, y] = transformPointsForward(tform, u, v); 
dx = x(2) - x(1); 
dy = y(2) - y(1); 
angle = (180/pi) * atan2(dy, dx) 

angle = 29.7686

scale = 1 / sqrt(dx^2 + dy^2)

scale = 1.0003

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

• affine2d supports the generation of C code (requires MATLAB^® Coder™). For more information, see Code Generation for Image Processing.

• When generating code, you can only specify singular objects—arrays of objects are not supported.

GPU Code Generation

Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Usage notes and limitations:

• When generating code, you can only specify singular objects—arrays of objects are not supported.

Thread-Based Environment

Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.

This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.

Version History

Introduced in R2013a