estimateAffine2D

geometryfunctionOpenCV 5.0.0

import { estimateAffine2D } from '@banou/opencv-wasm'

Use after await initOpenCV(). See the initialization and named imports guide.

Explore visually: Affine transformations →

Map points with a linear transform plus translation, preserving straight lines and parallelism.

VISUAL WALKTHROUGHGeometry

REFERENCE INPUTSource coordinate frame

This example applies a known rotation, scale and translation to the source.

→

RESULTResampled output

The output preserves straight lines under this affine transform. Locations outside the source need an explicit border rule.

Illustrative example. The stages explain the method; they are not a live OpenCV execution.

Computes an optimal affine transformation between two 2D point sets.

It computes

\begin{bmatrix}
x\\
y\\
\end{bmatrix}
=
\begin{bmatrix}
a_{11} & a_{12}\\
a_{21} & a_{22}\\
\end{bmatrix}
\begin{bmatrix}
X\\
Y\\
\end{bmatrix}
+
\begin{bmatrix}
b_1\\
b_2\\
\end{bmatrix}

Note: The RANSAC method can handle practically any ratio of outliers but needs a threshold to distinguish inliers from outliers. The method LMeDS does not need any threshold but it works correctly only when there are more than 50% of inliers.

See: estimateAffinePartial2D, getAffineTransform

estimateAffine2D(from_: Mat, to: Mat, inliers: Mat, method: number, ransacReprojThreshold: number, maxIters: number, confidence: number, refineIters: number): Mat;

7 available overloads

estimateAffine2D(from_: Mat, to: Mat): Mat;

estimateAffine2D(from_: Mat, to: Mat, inliers: Mat): Mat;

estimateAffine2D(from_: Mat, to: Mat, inliers: Mat, method: number): Mat;

estimateAffine2D(from_: Mat, to: Mat, inliers: Mat, method: number, ransacReprojThreshold: number): Mat;

estimateAffine2D(from_: Mat, to: Mat, inliers: Mat, method: number, ransacReprojThreshold: number, maxIters: number): Mat;

estimateAffine2D(from_: Mat, to: Mat, inliers: Mat, method: number, ransacReprojThreshold: number, maxIters: number, confidence: number): Mat;

estimateAffine2D(from_: Mat, to: Mat, inliers: Mat, method: number, ransacReprojThreshold: number, maxIters: number, confidence: number, refineIters: number): Mat;

from_

First input 2D point set containing (X,Y).

to

Second input 2D point set containing (x,y).

inliers

Output destination, filled by the native operation. Output vector indicating which points are inliers (1-inlier, 0-outlier).

method

Robust method used to compute transformation. The following methods are possible:

• RANSAC - RANSAC-based robust method
• LMEDS - Least-Median robust method RANSAC is the default method.

ransacReprojThreshold

Maximum reprojection error in the RANSAC algorithm to consider a point as an inlier. Applies only to RANSAC.

maxIters

The maximum number of robust method iterations.

confidence

Confidence level, between 0 and 1, for the estimated transformation. Anything between 0.95 and 0.99 is usually good enough. Values too close to 1 can slow down the estimation significantly. Values lower than 0.8-0.9 can result in an incorrectly estimated transformation.

refineIters

Maximum number of iterations of refining algorithm (Levenberg-Marquardt). Passing 0 will disable refining, so the output matrix will be output of robust method.

Returns

Output 2D affine transformation matrix 2 \times 3 or empty matrix if transformation could not be estimated. The returned matrix has the following form:

\begin{bmatrix}
a_{11} & a_{12} & b_1\\
a_{21} & a_{22} & b_2\\
\end{bmatrix}

The function estimates an optimal 2D affine transformation between two 2D point sets using the selected robust algorithm.

The computed transformation is then refined further (using only inliers) with the Levenberg-Marquardt method to reduce the re-projection error even more. Release returned native handles with using or delete(), including handles nested in results.

Upstream declaration ↗

These signatures describe this package. Upstream documentation can mention optional backends that are absent from this build. Check runtime compatibility before choosing a backend or file format.