detectCircleGridPoints

Detect circle grid pattern in images

Since R2021b

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Syntax

imagePoints = detectCircleGridPoints(I,patternDims)
[imagePoints,imagesUsed] = detectCircleGridPoints(imageFileNames,patternDims)
[___] = detectCircleGridPoints(images,patternDims)
[imagePoints,pairsUsed] = detectCircleGridPoints(imageFileNames1,imageFileNames2,patternDims)
[___] = detectCircleGridPoints(images1,images2,patternDims)
[___] = detectCircleGridPoints(___,Name=Value)

Description

Single Image Circle Grid Detection

imagePoints = detectCircleGridPoints(I,patternDims) detects a circle grid in a 2-D truecolor or grayscale image, I. For more details on circle grid patterns, see Circle Grid Patterns.

example

[imagePoints,imagesUsed] = detectCircleGridPoints(imageFileNames,patternDims) detects a circle grid in the image files specified by imageFileNames, and additionally returns the list of images in which the circle grid is detected imagesUsed.

[___] = detectCircleGridPoints(images,patternDims) detects a circle grid in the specified images images.

Stereo Pair Circle Grid Detection

[imagePoints,pairsUsed] = detectCircleGridPoints(imageFileNames1,imageFileNames2,patternDims) detects a circle grid in the stereo pairs of image files specified by imageFileNames1 and imageFileNames2. The function additionally returns a list of the pairs in which the pattern is detected pairsUsed.

example

[___] = detectCircleGridPoints(images1,images2,patternDims) detects a circle grid in the stereo pairs of image files specified by images1 and images2.

Optional Arguments

[___] = detectCircleGridPoints(___,Name=Value) specifies options using one or more name-value arguments in addition to any combination of arguments from previous syntaxes. For example, detectCircleGridPoints(I,patternDims,PatternType="symmetric") detects a symmetric circle grid in the specified workspace.

Examples

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Open Live Script

Load an image containing a circle grid pattern into the workspace.

imageFileName = fullfile(toolboxdir("vision"),"visiondata", ...
                "calibration","circleGrid","mono","image08.jpg");
I = imread(imageFileName);

Define the dimensions for the circle grid pattern.

patternDims = [8 11];

Detect the circle grid points.

imagePoints = detectCircleGridPoints(I,patternDims,PatternType="symmetric")
imagePoints = 88×2

  395.1729  358.4451
  383.5573  388.4410
  370.8857  420.9698
  356.9887  456.5418
  341.6686  495.7388
  325.0617  538.9151
  306.5055  586.8763
  285.8323  640.1285
  436.4195  363.5016
  426.5806  393.4896
  415.9378  426.1730
  404.2823  461.8252
  391.4709  500.9889
  377.3850  543.9532
  361.7202  591.7051
      ⋮

Display the detected points on the image.

J = insertText(I,imagePoints,1:size(imagePoints,1));
J = insertMarker(J,imagePoints,"x",MarkerColor="green",Size=5);
imshow(J)
title("Detected a Circle Grid of Dimensions" + mat2str(patternDims))

Figure contains an axes object. The hidden axes object with title Detected a Circle Grid of Dimensions[8 11] contains an object of type image.

Open Live Script

Specify your calibration images.

imageDir = fullfile(toolboxdir('vision'),'visiondata', ...
                            'calibration','circleGrid','stereo');
leftImages = imageDatastore(fullfile(imageDir,'left'));
rightImages = imageDatastore(fullfile(imageDir,'right'));
images1 = leftImages.Files;
images2 = rightImages.Files;

Define the dimensions for the circle grid pattern.

patternDims = [4 11];

Detect the circle grid points in the images.

[imagePoints,pairsUsed] = detectCircleGridPoints(images1,images2,patternDims);

Display the points from the first four images of camera one.

figure
t1 = tiledlayout(2,2,TileSpacing="compact",Padding="compact");
for i = 1:4
  nexttile
  imshow(images1{i}) 
  hold on
  plot(imagePoints(:,1,i,1),imagePoints(:,2,i,1),"gx");    
end
title(t1,"Camera 1")

Figure contains 4 axes objects. Hidden axes object 1 contains 2 objects of type image, line. One or more of the lines displays its values using only markers Hidden axes object 2 contains 2 objects of type image, line. One or more of the lines displays its values using only markers Hidden axes object 3 contains 2 objects of type image, line. One or more of the lines displays its values using only markers Hidden axes object 4 contains 2 objects of type image, line. One or more of the lines displays its values using only markers

Display points from the first four images from camera two.

images2 = images2(pairsUsed);
figure
t2 = tiledlayout(2,2,TileSpacing="compact",Padding="compact");
for i = 1:4
  nexttile
  imshow(images2{i}) 
  hold on
  plot(imagePoints(:,1,i,2),imagePoints(:,2,i,2),"gx");    
end
title(t2,"Camera 2")

Figure contains 4 axes objects. Hidden axes object 1 contains 2 objects of type image, line. One or more of the lines displays its values using only markers Hidden axes object 2 contains 2 objects of type image, line. One or more of the lines displays its values using only markers Hidden axes object 3 contains 2 objects of type image, line. One or more of the lines displays its values using only markers Hidden axes object 4 contains 2 objects of type image, line. One or more of the lines displays its values using only markers

Input Arguments

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Pattern dimensions, specified as a two-element vector that represents the number of circles in the x and y dimensions of the image, respectively. For more details on circle grid patterns, see Circle Grid Patterns.

AsymmetricSymmetric

Asymmetric grid

Symmetric grid

Image, specified as a 2-D truecolor image or grayscale image.

Data Types: uint8 | int16 | uint16 | single | double

Images, specified as an H-by-W-by-numColorChannels-by-numImages array, where H and W describe the height and width of each image, respectively. numColorChannels is the number of color channels in each image, and numImages is the number of images.

Data Types: uint8 | int16 | uint16 | single | double

Stereo pair images from camera one, specified as an H-by-W-by-numColorChannels-by-numImages array, where H and W describe the height and width of each image, respectively. numColorChannels is the number of color channels in each image, and numImages is the number of images

Data Types: uint8 | int16 | uint16 | single | double

Stereo pair images from camera two, specified as an H-by-W-by-numColorChannels-by-numImages array, where H and W describe the height and width of each image, respectively. numColorChannels is the number of color channels in each image, and numImages is the number of images

Data Types: uint8 | int16 | uint16 | single | double

Image file names, specified as a cell array of character vectors or an array of strings.

Stereo image file names for camera one, specified as a cell array of character vectors or an array of strings.

Stereo image file names for camera two, specified as a cell array of character vectors or an array of strings.

Name-Value Arguments

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Example: detectCircleGridPoints(I,patternDims,PatternType="symmetric") detects a symmetric circle grid in the specified workspace.

Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Circle grid pattern type, specified as "asymmetric" or "symmetric".

Circle color, specified as "black" or "white". Choose the color for the circle that has the strongest contrast with the background.

Output Arguments

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Center coordinates of detected circle grid, returned as an M-by-2 matrix or an M-by-2-by-numPairs-by-2 array. M is the number of circle grids detected, calculated as the product of the number of circle grids detected in each dimension. Each row of the matrix or array specifies the x-y coordinates of the center of a circle grid.

  • For single images — This argument is an M-by-2 matrix when detecting circle grids in single images.

  • For stereo pairs — This argument is an M-by-2-by-numPairs-by-2 array when detecting circle grids in stereo pairs of images. numPairs is the number of image pairs in which a circle grid is detected. imagePoints(:,:,:,1) returns the points from the first set of images, and imagePoints(:,:,:,2) are the points from the second set.

Pattern detection flag, returned as a logical vector. A value of true in the imagesUsed vector indicates that the pattern has been detected in the corresponding image.

Stereo pair pattern detection flag, returned as a logical vector. A value of true in the pairsUsed vector indicates that the pattern has been detected in the corresponding image pair.

Algorithms

For a circle grid pattern to be detected, the pattern must:

  • Contain at least 16 circles

  • Be fully visible in the image of a single camera or in both images of a pair of stereo cameras

Version History

Introduced in R2021b

See Also

Apps

Functions

Objects

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