OpenCV  4.6.0-dev Open Source Computer Vision
cv::aruco::DetectorParameters Struct Reference

struct DetectorParameters is used by ArucoDetector More...

#include <opencv2/aruco_detector.hpp>

## Public Member Functions

DetectorParameters ()

Read a new set of DetectorParameters from FileNode (use FileStorage.root()). More...

bool writeDetectorParameters (const Ptr< FileStorage > &fs)
Write a set of DetectorParameters to FileStorage. More...

## Static Public Member Functions

static Ptr< DetectorParameterscreate ()
Create a new set of DetectorParameters with default values. More...

## Public Attributes

constant for adaptive thresholding before finding contours (default 7) More...

maximum window size for adaptive thresholding before finding contours (default 23). More...

minimum window size for adaptive thresholding before finding contours (default 3). More...

reject quads where pairs of edges have angles that are close to straight or close to 180 degrees. Zero means that no quads are rejected. (In radians) (default 10*PI/180) More...

int aprilTagDeglitch
should the thresholded image be deglitched? Only useful for very noisy images (default 0). More...

float aprilTagMaxLineFitMse
when fitting lines to the contours, what is the maximum mean squared error More...

int aprilTagMaxNmaxima
how many corner candidates to consider when segmenting a group of pixels into a quad (default 10). More...

int aprilTagMinClusterPixels
reject quads containing too few pixels (default 5). More...

int aprilTagMinWhiteBlackDiff
when we build our model of black & white pixels, we add an extra check that the white model must be (overall) brighter than the black model. How much brighter? (in pixel values, [0,255]). (default 5) More...

April :: User-configurable parameters. detection of quads can be done on a lower-resolution image, improving speed at a cost of pose accuracy and a slight decrease in detection rate. Decoding the binary payload is still. More...

what Gaussian blur should be applied to the segmented image (used for quad detection?) More...

int cornerRefinementMaxIterations
maximum number of iterations for stop criteria of the corner refinement process (default 30). More...

int cornerRefinementMethod
default CORNER_REFINE_NONE. 0:CORNER_REFINE_NONE, no refinement. 1: CORNER_REFINE_SUBPIX, do subpixel refinement. 2: CORNER_REFINE_CONTOUR use contour-Points, 3: CORNER_REFINE_APRILTAG use the AprilTag2 approach). More...

double cornerRefinementMinAccuracy
minimum error for the stop cristeria of the corner refinement process (default: 0.1) More...

int cornerRefinementWinSize
window size for the corner refinement process (in pixels) (default 5). More...

bool detectInvertedMarker
to check if there is a white marker. In order to generate a "white" marker just invert a normal marker by using a tilde, ~markerImage. (default false) More...

double errorCorrectionRate
error correction rate respect to the maximun error correction capability for each dictionary (default 0.6). More...

int markerBorderBits
number of bits of the marker border, i.e. marker border width (default 1). More...

double maxErroneousBitsInBorderRate
maximum number of accepted erroneous bits in the border (i.e. number of allowed white bits in the border). Represented as a rate respect to the total number of bits per marker (default 0.35). More...

double maxMarkerPerimeterRate
determine maximum perimeter for marker contour to be detected. This is defined as a rate respect to the maximum dimension of the input image (default 4.0). More...

double minCornerDistanceRate
minimum distance between corners for detected markers relative to its perimeter (default 0.05) More...

int minDistanceToBorder
minimum distance of any corner to the image border for detected markers (in pixels) (default 3) More...

double minMarkerDistanceRate
minimum mean distance beetween two marker corners to be considered imilar, so that the smaller one is removed. The rate is relative to the smaller perimeter of the two markers (default 0.05). More...

float minMarkerLengthRatioOriginalImg
range [0,1], eq (2) from paper. The parameter tau_i has a direct influence on the processing speed. More...

double minMarkerPerimeterRate
determine minimum perimeter for marker contour to be detected. This is defined as a rate respect to the maximum dimension of the input image (default 0.03). More...

double minOtsuStdDev
minimun standard deviation in pixels values during the decodification step to apply Otsu thresholding (otherwise, all the bits are set to 0 or 1 depending on mean higher than 128 or not) (default 5.0) More...

int minSideLengthCanonicalImg
minimum side length of a marker in the canonical image. Latter is the binarized image in which contours are searched. More...

double perspectiveRemoveIgnoredMarginPerCell
width of the margin of pixels on each cell not considered for the determination of the cell bit. Represents the rate respect to the total size of the cell, i.e. perspectiveRemovePixelPerCell (default 0.13) More...

int perspectiveRemovePixelPerCell
number of bits (per dimension) for each cell of the marker when removing the perspective (default 4). More...

double polygonalApproxAccuracyRate
minimum accuracy during the polygonal approximation process to determine which contours are squares. (default 0.03) More...

bool useAruco3Detection
new Aruco functionality proposed in the paper: Romero-Ramirez et al: Speeded up detection of squared fiducial markers (2018) https://www.researchgate.net/publication/325787310_Speeded_Up_Detection_of_Squared_Fiducial_Markers More...

## Detailed Description

struct DetectorParameters is used by ArucoDetector

## ◆ DetectorParameters()

 cv::aruco::DetectorParameters::DetectorParameters ( )
inline

## ◆ create()

 static Ptr cv::aruco::DetectorParameters::create ( )
inlinestatic

Create a new set of DetectorParameters with default values.

 bool cv::aruco::DetectorParameters::readDetectorParameters ( const FileNode & fn )

Read a new set of DetectorParameters from FileNode (use FileStorage.root()).

## ◆ writeDetectorParameters()

 bool cv::aruco::DetectorParameters::writeDetectorParameters ( const Ptr< FileStorage > & fs )

Write a set of DetectorParameters to FileStorage.

## Member Data Documentation

constant for adaptive thresholding before finding contours (default 7)

maximum window size for adaptive thresholding before finding contours (default 23).

minimum window size for adaptive thresholding before finding contours (default 3).

reject quads where pairs of edges have angles that are close to straight or close to 180 degrees. Zero means that no quads are rejected. (In radians) (default 10*PI/180)

## ◆ aprilTagDeglitch

 int cv::aruco::DetectorParameters::aprilTagDeglitch

should the thresholded image be deglitched? Only useful for very noisy images (default 0).

## ◆ aprilTagMaxLineFitMse

 float cv::aruco::DetectorParameters::aprilTagMaxLineFitMse

when fitting lines to the contours, what is the maximum mean squared error

## ◆ aprilTagMaxNmaxima

 int cv::aruco::DetectorParameters::aprilTagMaxNmaxima

how many corner candidates to consider when segmenting a group of pixels into a quad (default 10).

## ◆ aprilTagMinClusterPixels

 int cv::aruco::DetectorParameters::aprilTagMinClusterPixels

reject quads containing too few pixels (default 5).

## ◆ aprilTagMinWhiteBlackDiff

 int cv::aruco::DetectorParameters::aprilTagMinWhiteBlackDiff

when we build our model of black & white pixels, we add an extra check that the white model must be (overall) brighter than the black model. How much brighter? (in pixel values, [0,255]). (default 5)

April :: User-configurable parameters. detection of quads can be done on a lower-resolution image, improving speed at a cost of pose accuracy and a slight decrease in detection rate. Decoding the binary payload is still.

what Gaussian blur should be applied to the segmented image (used for quad detection?)

## ◆ cornerRefinementMaxIterations

 int cv::aruco::DetectorParameters::cornerRefinementMaxIterations

maximum number of iterations for stop criteria of the corner refinement process (default 30).

## ◆ cornerRefinementMethod

 int cv::aruco::DetectorParameters::cornerRefinementMethod

default CORNER_REFINE_NONE. 0:CORNER_REFINE_NONE, no refinement. 1: CORNER_REFINE_SUBPIX, do subpixel refinement. 2: CORNER_REFINE_CONTOUR use contour-Points, 3: CORNER_REFINE_APRILTAG use the AprilTag2 approach).

## ◆ cornerRefinementMinAccuracy

 double cv::aruco::DetectorParameters::cornerRefinementMinAccuracy

minimum error for the stop cristeria of the corner refinement process (default: 0.1)

## ◆ cornerRefinementWinSize

 int cv::aruco::DetectorParameters::cornerRefinementWinSize

window size for the corner refinement process (in pixels) (default 5).

## ◆ detectInvertedMarker

 bool cv::aruco::DetectorParameters::detectInvertedMarker

to check if there is a white marker. In order to generate a "white" marker just invert a normal marker by using a tilde, ~markerImage. (default false)

## ◆ errorCorrectionRate

 double cv::aruco::DetectorParameters::errorCorrectionRate

error correction rate respect to the maximun error correction capability for each dictionary (default 0.6).

## ◆ markerBorderBits

 int cv::aruco::DetectorParameters::markerBorderBits

number of bits of the marker border, i.e. marker border width (default 1).

## ◆ maxErroneousBitsInBorderRate

 double cv::aruco::DetectorParameters::maxErroneousBitsInBorderRate

maximum number of accepted erroneous bits in the border (i.e. number of allowed white bits in the border). Represented as a rate respect to the total number of bits per marker (default 0.35).

## ◆ maxMarkerPerimeterRate

 double cv::aruco::DetectorParameters::maxMarkerPerimeterRate

determine maximum perimeter for marker contour to be detected. This is defined as a rate respect to the maximum dimension of the input image (default 4.0).

## ◆ minCornerDistanceRate

 double cv::aruco::DetectorParameters::minCornerDistanceRate

minimum distance between corners for detected markers relative to its perimeter (default 0.05)

## ◆ minDistanceToBorder

 int cv::aruco::DetectorParameters::minDistanceToBorder

minimum distance of any corner to the image border for detected markers (in pixels) (default 3)

## ◆ minMarkerDistanceRate

 double cv::aruco::DetectorParameters::minMarkerDistanceRate

minimum mean distance beetween two marker corners to be considered imilar, so that the smaller one is removed. The rate is relative to the smaller perimeter of the two markers (default 0.05).

## ◆ minMarkerLengthRatioOriginalImg

 float cv::aruco::DetectorParameters::minMarkerLengthRatioOriginalImg

range [0,1], eq (2) from paper. The parameter tau_i has a direct influence on the processing speed.

## ◆ minMarkerPerimeterRate

 double cv::aruco::DetectorParameters::minMarkerPerimeterRate

determine minimum perimeter for marker contour to be detected. This is defined as a rate respect to the maximum dimension of the input image (default 0.03).

## ◆ minOtsuStdDev

 double cv::aruco::DetectorParameters::minOtsuStdDev

minimun standard deviation in pixels values during the decodification step to apply Otsu thresholding (otherwise, all the bits are set to 0 or 1 depending on mean higher than 128 or not) (default 5.0)

## ◆ minSideLengthCanonicalImg

 int cv::aruco::DetectorParameters::minSideLengthCanonicalImg

minimum side length of a marker in the canonical image. Latter is the binarized image in which contours are searched.

## ◆ perspectiveRemoveIgnoredMarginPerCell

 double cv::aruco::DetectorParameters::perspectiveRemoveIgnoredMarginPerCell

width of the margin of pixels on each cell not considered for the determination of the cell bit. Represents the rate respect to the total size of the cell, i.e. perspectiveRemovePixelPerCell (default 0.13)

## ◆ perspectiveRemovePixelPerCell

 int cv::aruco::DetectorParameters::perspectiveRemovePixelPerCell

number of bits (per dimension) for each cell of the marker when removing the perspective (default 4).

## ◆ polygonalApproxAccuracyRate

 double cv::aruco::DetectorParameters::polygonalApproxAccuracyRate

minimum accuracy during the polygonal approximation process to determine which contours are squares. (default 0.03)

## ◆ useAruco3Detection

 bool cv::aruco::DetectorParameters::useAruco3Detection

new Aruco functionality proposed in the paper: Romero-Ramirez et al: Speeded up detection of squared fiducial markers (2018) https://www.researchgate.net/publication/325787310_Speeded_Up_Detection_of_Squared_Fiducial_Markers

to enable the new and faster Aruco detection strategy.

The documentation for this struct was generated from the following file: