EstervQrCode
1.1.1
Library for qr code manipulation
struct DetectorParameters is used by ArucoDetector More...
#include <aruco_detector.hpp>
Public Member Functions | |
| CV_WRAP | DetectorParameters () |
| CV_WRAP bool | readDetectorParameters (const FileNode &fn) |
| Read a new set of DetectorParameters from FileNode (use FileStorage.root()). More... | |
| CV_WRAP bool | writeDetectorParameters (FileStorage &fs, const String &name=String()) |
| Write a set of DetectorParameters to FileStorage. More... | |
Public Attributes | |
| CV_PROP_RW int | adaptiveThreshWinSizeMin |
| minimum window size for adaptive thresholding before finding contours (default 3). More... | |
| CV_PROP_RW int | adaptiveThreshWinSizeMax |
| maximum window size for adaptive thresholding before finding contours (default 23). More... | |
| CV_PROP_RW int | adaptiveThreshWinSizeStep |
| increments from adaptiveThreshWinSizeMin to adaptiveThreshWinSizeMax during the thresholding (default 10). More... | |
| CV_PROP_RW double | adaptiveThreshConstant |
| constant for adaptive thresholding before finding contours (default 7) More... | |
| CV_PROP_RW double | minMarkerPerimeterRate |
| determine minimum perimeter for marker contour to be detected. More... | |
| CV_PROP_RW double | maxMarkerPerimeterRate |
| determine maximum perimeter for marker contour to be detected. More... | |
| CV_PROP_RW double | polygonalApproxAccuracyRate |
| minimum accuracy during the polygonal approximation process to determine which contours are squares. (default 0.03) More... | |
| CV_PROP_RW double | minCornerDistanceRate |
| minimum distance between corners for detected markers relative to its perimeter (default 0.05) More... | |
| CV_PROP_RW int | minDistanceToBorder |
| minimum distance of any corner to the image border for detected markers (in pixels) (default 3) More... | |
| CV_PROP_RW double | minMarkerDistanceRate |
| minimum average distance between the corners of the two markers to be grouped (default 0.125). More... | |
| CV_PROP_RW float | minGroupDistance = 0.21f |
| minimum average distance between the corners of the two markers in group to add them to the list of candidates More... | |
| CV_PROP_RW int | cornerRefinementMethod |
| default value CORNER_REFINE_NONE More... | |
| CV_PROP_RW int | cornerRefinementWinSize |
| maximum window size for the corner refinement process (in pixels) (default 5). More... | |
| CV_PROP_RW float | relativeCornerRefinmentWinSize |
| Dynamic window size for corner refinement relative to Aruco module size (default 0.3). More... | |
| CV_PROP_RW int | cornerRefinementMaxIterations |
| maximum number of iterations for stop criteria of the corner refinement process (default 30). More... | |
| CV_PROP_RW double | cornerRefinementMinAccuracy |
| minimum error for the stop cristeria of the corner refinement process (default: 0.1) More... | |
| CV_PROP_RW int | markerBorderBits |
| number of bits of the marker border, i.e. marker border width (default 1). More... | |
| CV_PROP_RW int | perspectiveRemovePixelPerCell |
| number of bits (per dimension) for each cell of the marker when removing the perspective (default 4). More... | |
| CV_PROP_RW double | perspectiveRemoveIgnoredMarginPerCell |
| width of the margin of pixels on each cell not considered for the determination of the cell bit. More... | |
| CV_PROP_RW double | maxErroneousBitsInBorderRate |
| maximum number of accepted erroneous bits in the border (i.e. number of allowed white bits in the border). More... | |
| CV_PROP_RW 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... | |
| CV_PROP_RW double | errorCorrectionRate |
| error correction rate respect to the maximun error correction capability for each dictionary (default 0.6). More... | |
| CV_PROP_RW float | aprilTagQuadDecimate |
| April :: User-configurable parameters. More... | |
| CV_PROP_RW float | aprilTagQuadSigma |
| what Gaussian blur should be applied to the segmented image (used for quad detection?) More... | |
| CV_PROP_RW int | aprilTagMinClusterPixels |
| reject quads containing too few pixels (default 5). More... | |
| CV_PROP_RW int | aprilTagMaxNmaxima |
| how many corner candidates to consider when segmenting a group of pixels into a quad (default 10). More... | |
| CV_PROP_RW float | aprilTagCriticalRad |
| reject quads where pairs of edges have angles that are close to straight or close to 180 degrees. More... | |
| CV_PROP_RW float | aprilTagMaxLineFitMse |
| when fitting lines to the contours, what is the maximum mean squared error More... | |
| CV_PROP_RW int | aprilTagMinWhiteBlackDiff |
| add an extra check that the white model must be (overall) brighter than the black model. More... | |
| CV_PROP_RW int | aprilTagDeglitch |
| should the thresholded image be deglitched? Only useful for very noisy images (default 0). More... | |
| CV_PROP_RW bool | detectInvertedMarker |
| to check if there is a white marker. More... | |
| CV_PROP_RW bool | useAruco3Detection |
| enable the new and faster Aruco detection strategy. More... | |
| CV_PROP_RW int | minSideLengthCanonicalImg |
| minimum side length of a marker in the canonical image. Latter is the binarized image in which contours are searched. More... | |
| CV_PROP_RW float | minMarkerLengthRatioOriginalImg |
| range [0,1], eq (2) from paper. The parameter tau_i has a direct influence on the processing speed. More... | |
struct DetectorParameters is used by ArucoDetector
|
inline |
Read a new set of DetectorParameters from FileNode (use FileStorage.root()).
| CV_WRAP bool cv::aruco::DetectorParameters::writeDetectorParameters | ( | FileStorage & | fs, |
| const String & | name = String() |
||
| ) |
Write a set of DetectorParameters to FileStorage.
| CV_PROP_RW double cv::aruco::DetectorParameters::adaptiveThreshConstant |
constant for adaptive thresholding before finding contours (default 7)
| CV_PROP_RW int cv::aruco::DetectorParameters::adaptiveThreshWinSizeMax |
maximum window size for adaptive thresholding before finding contours (default 23).
| CV_PROP_RW int cv::aruco::DetectorParameters::adaptiveThreshWinSizeMin |
minimum window size for adaptive thresholding before finding contours (default 3).
| CV_PROP_RW int cv::aruco::DetectorParameters::adaptiveThreshWinSizeStep |
increments from adaptiveThreshWinSizeMin to adaptiveThreshWinSizeMax during the thresholding (default 10).
| CV_PROP_RW float cv::aruco::DetectorParameters::aprilTagCriticalRad |
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)
| CV_PROP_RW int cv::aruco::DetectorParameters::aprilTagDeglitch |
should the thresholded image be deglitched? Only useful for very noisy images (default 0).
| CV_PROP_RW float cv::aruco::DetectorParameters::aprilTagMaxLineFitMse |
when fitting lines to the contours, what is the maximum mean squared error
| CV_PROP_RW int cv::aruco::DetectorParameters::aprilTagMaxNmaxima |
how many corner candidates to consider when segmenting a group of pixels into a quad (default 10).
| CV_PROP_RW int cv::aruco::DetectorParameters::aprilTagMinClusterPixels |
reject quads containing too few pixels (default 5).
| CV_PROP_RW int cv::aruco::DetectorParameters::aprilTagMinWhiteBlackDiff |
add an extra check that the white model must be (overall) brighter than the black model.
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)
| CV_PROP_RW float cv::aruco::DetectorParameters::aprilTagQuadDecimate |
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
| CV_PROP_RW float cv::aruco::DetectorParameters::aprilTagQuadSigma |
what Gaussian blur should be applied to the segmented image (used for quad detection?)
| CV_PROP_RW int cv::aruco::DetectorParameters::cornerRefinementMaxIterations |
maximum number of iterations for stop criteria of the corner refinement process (default 30).
| CV_PROP_RW int cv::aruco::DetectorParameters::cornerRefinementMethod |
default value CORNER_REFINE_NONE
| CV_PROP_RW double cv::aruco::DetectorParameters::cornerRefinementMinAccuracy |
minimum error for the stop cristeria of the corner refinement process (default: 0.1)
| CV_PROP_RW int cv::aruco::DetectorParameters::cornerRefinementWinSize |
maximum window size for the corner refinement process (in pixels) (default 5).
The window size may decrease if the ArUco marker is too small, check relativeCornerRefinmentWinSize. The final window size is calculated as: min(cornerRefinementWinSize, averageArucoModuleSize*relativeCornerRefinmentWinSize), where averageArucoModuleSize is average module size of ArUco marker in pixels. (ArUco marker is composed of black and white modules)
| CV_PROP_RW 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)
| CV_PROP_RW double cv::aruco::DetectorParameters::errorCorrectionRate |
error correction rate respect to the maximun error correction capability for each dictionary (default 0.6).
| CV_PROP_RW int cv::aruco::DetectorParameters::markerBorderBits |
number of bits of the marker border, i.e. marker border width (default 1).
| CV_PROP_RW 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).
| CV_PROP_RW 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).
| CV_PROP_RW double cv::aruco::DetectorParameters::minCornerDistanceRate |
minimum distance between corners for detected markers relative to its perimeter (default 0.05)
| CV_PROP_RW int cv::aruco::DetectorParameters::minDistanceToBorder |
minimum distance of any corner to the image border for detected markers (in pixels) (default 3)
| CV_PROP_RW float cv::aruco::DetectorParameters::minGroupDistance = 0.21f |
minimum average distance between the corners of the two markers in group to add them to the list of candidates
The average distance between the corners of the two markers is calculated relative to its module size (default 0.21).
| CV_PROP_RW double cv::aruco::DetectorParameters::minMarkerDistanceRate |
minimum average distance between the corners of the two markers to be grouped (default 0.125).
The rate is relative to the smaller perimeter of the two markers. Two markers are grouped if average distance between the corners of the two markers is less than min(MarkerPerimeter1, MarkerPerimeter2)*minMarkerDistanceRate.
default value is 0.125 because 0.125*MarkerPerimeter = (MarkerPerimeter / 4) * 0.5 = half the side of the marker.
| CV_PROP_RW float cv::aruco::DetectorParameters::minMarkerLengthRatioOriginalImg |
range [0,1], eq (2) from paper. The parameter tau_i has a direct influence on the processing speed.
| CV_PROP_RW 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).
| CV_PROP_RW 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)
| CV_PROP_RW 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.
| CV_PROP_RW 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)
| CV_PROP_RW int cv::aruco::DetectorParameters::perspectiveRemovePixelPerCell |
number of bits (per dimension) for each cell of the marker when removing the perspective (default 4).
| CV_PROP_RW double cv::aruco::DetectorParameters::polygonalApproxAccuracyRate |
minimum accuracy during the polygonal approximation process to determine which contours are squares. (default 0.03)
| CV_PROP_RW float cv::aruco::DetectorParameters::relativeCornerRefinmentWinSize |
Dynamic window size for corner refinement relative to Aruco module size (default 0.3).
The final window size is calculated as: min(cornerRefinementWinSize, averageArucoModuleSize*relativeCornerRefinmentWinSize), where averageArucoModuleSize is average module size of ArUco marker in pixels. (ArUco marker is composed of black and white modules) In the case of markers located far from each other, it may be useful to increase the value of the parameter to 0.4-0.5. In the case of markers located close to each other, it may be useful to decrease the parameter value to 0.1-0.2.
| CV_PROP_RW bool cv::aruco::DetectorParameters::useAruco3Detection |
enable the new and faster Aruco detection strategy.
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