boofcv.alg.fiducial.square

Class DetectFiducialSquareImage<T extends boofcv.struct.image.ImageGray<T>>

java.lang.Object

boofcv.alg.fiducial.square.BaseDetectFiducialSquare<T>

boofcv.alg.fiducial.square.DetectFiducialSquareImage<T>

public class DetectFiducialSquareImage<T extends boofcv.struct.image.ImageGray<T>>
extends BaseDetectFiducialSquare<T>

Fiducial which uses images to describe arbitrary binary patterns. When useing this fiducial it's up to the user to select good images which will provide unique orientation and are easily distinguished against other patterns and noise insensitive.

The above image visually shows the fiducials internal coordinate system. The center of the fiducial is the origin of the coordinate system, e.g. all sides are width/2 distance away from the origin. +x is to the right, +y is up , and +z out of the paper towards the viewer.

A good pattern will have thick lines or thick shapes. When detecting the image it's not uncommon for the distortion removal to be off by one or two pixels. So think lines are be completely out of synch. The image should also be chosen so that there is to rotational ambiguity. A perfect circle in the center is an example of a bad fiducial in which orientation can't be uniquely determined.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	DetectFiducialSquareImage.FiducialDef description of an image in 4 different orientations

Nested classes/interfaces inherited from class boofcv.alg.fiducial.square.BaseDetectFiducialSquare

BaseDetectFiducialSquare.Result

Field Summary

Fields inherited from class boofcv.alg.fiducial.square.BaseDetectFiducialSquare

borderWidthFraction, verbose

Constructor Summary

Constructors

Constructor and Description
DetectFiducialSquareImage(boofcv.abst.filter.binary.InputToBinary<T> inputToBinary, boofcv.alg.shapes.polygon.DetectPolygonBinaryGrayRefine<T> quadDetector, double borderWidthFraction, double minimumBlackBorderFraction, double matchThreshold, java.lang.Class<T> inputType) Configures the fiducial detector

Method Summary

Modifier and Type	Method and Description
int	addPattern(boofcv.struct.image.GrayU8 inputBinary, double lengthSide) Adds a new image to the detector.
protected static void	binaryToDef(boofcv.struct.image.GrayU8 binary, short[] desc) Converts a binary image into the compressed bit format
java.util.List<DetectFiducialSquareImage.FiducialDef>	getTargets()
protected int	hamming(short[] a, short[] b) Computes the hamming score between two descriptions.
protected boolean	processSquare(boofcv.struct.image.GrayF32 gray, BaseDetectFiducialSquare.Result result, double edgeInside, double edgeOutside) Processes the detected square and matches it to a known fiducial.

Methods inherited from class boofcv.alg.fiducial.square.BaseDetectFiducialSquare

computeFractionBoundary, configure, getBinary, getBorderWidthFraction, getFound, getInputType, getSquareDetector, getThresholdSideRatio, process, setThresholdSideRatio, setVerbose

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

DetectFiducialSquareImage

public DetectFiducialSquareImage(boofcv.abst.filter.binary.InputToBinary<T> inputToBinary,
                                 boofcv.alg.shapes.polygon.DetectPolygonBinaryGrayRefine<T> quadDetector,
                                 double borderWidthFraction,
                                 double minimumBlackBorderFraction,
                                 double matchThreshold,
                                 java.lang.Class<T> inputType)

Configures the fiducial detector

Parameters:

matchThreshold - Considered a match if the hamming distance is less than this fraction of the maximum

Method Detail

addPattern

public int addPattern(boofcv.struct.image.GrayU8 inputBinary,
                      double lengthSide)

Adds a new image to the detector. Image must be gray-scale and is converted into a binary image using the specified threshold. All input images are rescaled to be square and of the appropriate size. Thus the original shape of the image doesn't matter. Square shapes are highly recommended since that's what the target looks like.

Parameters:

inputBinary - Binary input image pattern. 0 = black, 1 = white.

lengthSide - How long one of the sides of the target is in world units.

Returns:

The ID of the provided image

binaryToDef

protected static void binaryToDef(boofcv.struct.image.GrayU8 binary,
                                  short[] desc)

Converts a binary image into the compressed bit format

processSquare

protected boolean processSquare(boofcv.struct.image.GrayF32 gray,
                                BaseDetectFiducialSquare.Result result,
                                double edgeInside,
                                double edgeOutside)

Description copied from class: BaseDetectFiducialSquare

Processes the detected square and matches it to a known fiducial. Black border is included.

Specified by:

processSquare in class BaseDetectFiducialSquare<T extends boofcv.struct.image.ImageGray<T>>

Parameters:

gray - Image of the undistorted square

result - Which target and its orientation was found

edgeInside - Average pixel value along edge inside

edgeOutside - Average pixel value along edge outside

Returns:

true if the square matches a known target.

hamming

protected int hamming(short[] a,
                      short[] b)

Computes the hamming score between two descriptions. Larger the number better the fit

getTargets

public java.util.List<DetectFiducialSquareImage.FiducialDef> getTargets()