public class FactoryOrientationAlgs
extends java.lang.Object
| Constructor and Description |
|---|
FactoryOrientationAlgs() |
| Modifier and Type | Method and Description |
|---|---|
static <II extends boofcv.struct.image.ImageGray> |
average_ii(ConfigAverageIntegral config,
java.lang.Class<II> integralType) |
static <T extends boofcv.struct.image.ImageGray> |
average(double objectToSample,
int radius,
boolean weighted,
java.lang.Class<T> derivType) |
static <T extends boofcv.struct.image.ImageGray> |
histogram(double objectToSample,
int numAngles,
int radius,
boolean weighted,
java.lang.Class<T> derivType) |
static <II extends boofcv.struct.image.ImageGray> |
image_ii(double objectRadiusToScale,
int sampleRadius,
double samplePeriod,
int sampleWidth,
double weightSigma,
java.lang.Class<II> integralImage)
Estimates the orientation without calculating the image derivative.
|
static <T extends boofcv.struct.image.ImageGray> |
nogradient(double objectToSample,
int radius,
java.lang.Class<T> imageType) |
static <D extends boofcv.struct.image.ImageGray> |
sift(ConfigSiftOrientation config,
java.lang.Class<D> derivType)
Estimates multiple orientations as specified in SIFT paper.
|
static <II extends boofcv.struct.image.ImageGray> |
sliding_ii(ConfigSlidingIntegral config,
java.lang.Class<II> integralType)
Estimates the orientation of a region by using a sliding window across the different potential
angles.
|
static <T extends boofcv.struct.image.ImageGray> |
sliding(double objectRadiusToScale,
int numAngles,
double windowSize,
int radius,
boolean weighted,
java.lang.Class<T> derivType) |
public static <T extends boofcv.struct.image.ImageGray> OrientationHistogram<T> histogram(double objectToSample, int numAngles, int radius, boolean weighted, java.lang.Class<T> derivType)
public static <T extends boofcv.struct.image.ImageGray> OrientationImageAverage<T> nogradient(double objectToSample, int radius, java.lang.Class<T> imageType)
public static <T extends boofcv.struct.image.ImageGray> OrientationAverage<T> average(double objectToSample, int radius, boolean weighted, java.lang.Class<T> derivType)
public static <T extends boofcv.struct.image.ImageGray> OrientationSlidingWindow<T> sliding(double objectRadiusToScale, int numAngles, double windowSize, int radius, boolean weighted, java.lang.Class<T> derivType)
public static <II extends boofcv.struct.image.ImageGray> OrientationIntegral<II> average_ii(ConfigAverageIntegral config, java.lang.Class<II> integralType)
config - Configuration for algorithm.integralType - Type of image being processed.ImplOrientationAverageGradientIntegralpublic static <II extends boofcv.struct.image.ImageGray> OrientationIntegral<II> image_ii(double objectRadiusToScale, int sampleRadius, double samplePeriod, int sampleWidth, double weightSigma, java.lang.Class<II> integralImage)
sampleRadius - Radius of the region being considered in terms of samples. Typically 6.samplePeriod - How often the image is sampled. This number is scaled. Typically 1.sampleWidth - How wide of a kernel should be used to sample. Try 4weightSigma - Sigma for weighting. zero for unweighted.integralImage - Type of image being processed.ImplOrientationImageAverageIntegralpublic static <II extends boofcv.struct.image.ImageGray> OrientationIntegral<II> sliding_ii(ConfigSlidingIntegral config, java.lang.Class<II> integralType)
config - Configuration for algorithm. If null defaults will be used.integralType - Type of integral image being processed.OrientationSlidingWindowpublic static <D extends boofcv.struct.image.ImageGray> OrientationHistogramSift<D> sift(ConfigSiftOrientation config, java.lang.Class<D> derivType)
config - Configuration for algorithm. If null defaults will be used.derivType - Type of derivative image it takes as input