cameraIntrinsicsFromOpenCV
Description
converts the OpenCV intrinsics, specified by the input arguments, into a MATLAB® object intrinsics
= cameraIntrinsicsFromOpenCV(intrinsicMatrix
,distortionCoefficients
,imageSize
)intrinsics
, which can be cameraIntrinsics
or cameraIntrinsicsKB
.
The OpenCV spatial coordinate system specifies the upper-left pixel center at
(0,0
), whereas the MATLAB spatial coordinate system specifies the pixel center at
(1,1
). The cameraIntrinsicsFromOpenCV
function
compensates for this difference by adding 1 to both of the x and
y-values for the converted principal point.
Examples
Undistort Image in MATLAB Using Camera Intrinsics from OpenCV
Define OpenCV camera intrinsic parameters in the workspace.
intrinsicMatrix = [729.4644 0 570.6455; 0 728.8196 346.0108; 0 0 1 ]; distortionCoefficients = [-0.4262 0.5460 0.0038 -0.0051 -0.6176];
Define the image size returned by the camera.
imageSize = [712 1072];
Convert the intrinsic parameters from OpenCV to MATLAB format.
intrinsics = cameraIntrinsicsFromOpenCV(intrinsicMatrix, ...
distortionCoefficients,imageSize);
Load the image to undistort.
filename = fullfile(toolboxdir("vision"),"visiondata","calibration", ... "mono","image01.jpg"); I = imread(filename);
Undistort the image and diplay the results.
J = undistortImage(I,intrinsics); imshowpair(I,J,"montage"); title("Original Image (left) vs. Corrected Image (right)");
Undistort Image Using Fisheye Camera Parameters from OpenCV
Define OpenCV fisheye parameters in the workspace.
intrinsicMatrix = [875.88 0.00 1005.62; ... 0.00 874.76 741.52; ... 0.00, 0.00, 1.00]; distortionCoeffs = [0.08, -0.16, 0.35, -0.26];
Define the image size returned by the camera.
imageSize =[1500 2000];
Import the intrinsic camera parameters for a fisheye lens from OpenCV.
intrinsicsKB = cameraIntrinsicsFromOpenCV(intrinsicMatrix,distortionCoeffs,imageSize)
intrinsicsKB = cameraIntrinsicsKB with properties: FocalLength: [875.8800 874.7600] PrincipalPoint: [1.0066e+03 742.5200] ImageSize: [1500 2000] DistortionCoefficients: [0.0800 -0.1600 0.3500 -0.2600] K: [3x3 double]
Load an image to undistort.
filename = fullfile(toolboxdir("vision"),"visiondata", ... "calibration","gopro","gopro01.jpg"); I = imread(filename);
Undistort the image and display the results.
J = undistortImage(I,intrinsicsKB); imshowpair(I,J,"montage"); title("Original Image (left) vs. Corrected Image (right)");
Import Camera Intrinsic Parameters from ROS
The ROS camera calibration package estimates camera intrinsic parameters using the OpenCV camera calibration tools [1]. After calibrating a camera in ROS, you can import its intrinsic parameters to a YAML file using the camera calibration parser in ROS. To use the calibrated camera with Computer Vision Toolbox™ functions, such as undistortImage
, you must read the camera parameters from the YAML file and then convert them into a cameraIntrinsics
object using cameraIntrinsicsFromOpenCV
.
Note: The cameraIntrinsicsFromOpenCV
function supports importing camera intrinsic parameters for only those pinhole camera models that use the ROS plumb-bob
distortion model.
Read Camera Intrinsic Parameters from a ROS YAML File
Read the camera parameters stored in cameraParams.yaml
using the helper function helperReadYAML
.
intrinsicsParams = helperReadYAML('cameraParams.yaml');
Create cameraIntrinsics
Object Using cameraIntrinsicsFromOpenCV
Use the cameraIntrinsicsFromOpenCV
function to create a cameraIntrinsics
object from the camera matrix and the distortion coefficients.
imageSize = [intrinsicsParams.image_height intrinsicsParams.image_width]; intrinsicMatrix = intrinsicsParams.camera_matrix; distortionCoefficients = intrinsicsParams.distortion_coefficients; intrinsicsObj = cameraIntrinsicsFromOpenCV(intrinsicMatrix,distortionCoefficients,imageSize);
Undistort Image
Use the imported camera intrinsics with undistortImage
to undistort an image captured using the calibrated camera.
% Load the captured image. imageName = fullfile(toolboxdir('vision'),'visiondata','calibration','stereo','left','left01.png'); I = imread(imageName); % Undistort the image. J = undistortImage(I,intrinsicsObj,'OutputView','full'); % Display the result. figure montage({I,J})
Supporting Functions
helperReadYAML
The helperReadYAML
function reads the monocular camera parameters from the input YAML file that was exported from ROS.
function cameraParams = helperReadYAML(filename) % helperReadYAML reads a ROS YAML file, filename, and returns a structure % with these fields: image_width, image_height, camera_name, % camera_matrix, distortion_model, distortion_coefficients, % rectification_matrix, and projection_matrix. These fields are stored % in the YAML file colon separated from their values in different lines. f = fopen(filename,'r'); stringFields = {'camera_name','distortion_model'}; while ~feof(f) [name,value,isEmptyLine] = helperReadYAMLLine(f); if isEmptyLine continue end if ~isempty(value) % Convert all values to numbers except for known string % fields. if ~any(contains(name, stringFields)) value = str2num(value); %#ok end else % An empty value in ROS YAML files indicates a matrix in % upcoming lines. Read the matrix from the upcoming lines. value = helperReadYAMLMatrix(f); end % Store post-processed value. cameraParams.(name) = value; end fclose(f); end
helperReadYAMLMatrix
The helperReadYAMLMatrix
function reads the rows, columns and data fields of a matrix in the ROS YAML file.
function matrix = helperReadYAMLMatrix(f) % helperReadYAMLMatrix reads a matrix from the ROS YAML file. A matrix in % a ROS YAML file has three fields: rows, columns and data. rows and col % describe the matrix size. data is a continguous array of the matrix % elements in row-major order. This helper function assumes the presence % of all three fields of a matrix to return the correct matrix. numRows = 0; numCols = 0; data = []; % Read numRows, numCols and matrix data. while ~feof(f) [name,value,isEmptyLine] = helperReadYAMLLine(f); if isEmptyLine continue end switch name case 'rows' numRows = str2num(value); %#ok case 'cols' numCols = str2num(value); %#ok case 'data' data = str2num(value); %#ok % Terminate the while loop as data is the last % field of a matrix in the ROS YAML file. break otherwise % Terminate the while loop if any other field is % encountered. break end end if numel(data) == numRows*numCols % Reshape the matrix using row-major order. matrix = reshape(data,[numCols numRows])'; end end
helperReadYAMLLine
The helperReadYAMLLine
function reads a line of a ROS YAML file.
function [name,value,isEmptyLine] = helperReadYAMLLine(f) % Read line from file. line = fgetl(f); % Trim leading and trailing whitespaces. line = strtrim(line); if isempty(line) || line(1)=='#' % Empty line or comment. name = ''; value = ''; isEmptyLine = true; else % Split the line to get name and value. c = strsplit(line,':'); assert(length(c)==2,'Unexpected file format') name = c{1}; value = strtrim(c{2}); % Trim leading whitespace. isEmptyLine = false; end end
References
Input Arguments
intrinsicMatrix
— Camera intrinsic matrix
3-by-3 matrix
Camera intrinsic matrix from OpenCV, specified as a 3-by-3 matrix of the form:
where fx and fy are the focal lengths in the x and y-directions, and (cx,cy) is the principal point in OpenCV.
distortionCoefficients
— Camera distortion coefficients
4-element vector | 5-element vector | 8-element vector
Camera distortion coefficients from OpenCV, specified as a 4-, 5-, or 8-element
vector. The function returns a cameraIntrinsics
object when using extended
pinhole model distortion coefficients and a cameraIntrinsicsKB
object for fisheye distortion coefficients.
Extended pinhole model — 5-element vector of the form [k1 k2 p1 p2 k3] or an 8-element vector of the form [k1 k2 p1 p2 k3 k4 k5 k6].
The values of k1, k2, …, k6 describe the radial distortion and p1 and p2 describe the tangential distortion, specified in OpenCV.
Kannala-Brandt model [1] — 4-element vector of the form [k1 k2 k3 k4]. These values are the distortion coefficients from the OpenCV fisheye camera model.
imageSize
— Image size
2-element vector
Image size, specified as a 2-element vector in the form [mrows,ncols].
Output Arguments
intrinsics
— Camera intrinsic parameters
cameraIntrinsics
object | cameraIntrinsicsKB
object
Camera intrinsic parameters, returned as a cameraIntrinsics
or cameraIntrinsicsKB
object. The function returns a cameraIntrinsics
object when using extended pinhole model distortion
coefficients and a cameraIntrinsicsKB
object for fisheye distortion coefficients.
cameraIntrinsics
object — Contains OpenCV intrinsics for a pinhole camera model. In cases where the OpenCV pinhole model uses more than eight distortion coefficients, which cannot be converted to acameraIntrinsics
object, you can recalibrate your camera using the Camera Calibrator app as an alternative solution.cameraIntrinsicsKB
object — Contains camera intrinsic calibration parameters for a fisheye lens, using the Kannala-Brandt model.
References
[1] Juho Kannala and Sami Brandt. A generic camera model and calibration method for conventional, wide-angle, and fish-eye lenses. IEEE transactions on pattern analysis and machine intelligence, 28:1335–40, 09 2006.
Version History
Introduced in R2021bR2024b: Import OpenCV pinhole camera model with six radial distortion coefficients
The cameraIntrinsicsFromOpenCV
has been updated to support OpenCV pinhole camera
model with 6 radial distortion coefficients.
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