## Class SIFT

• public class SIFT
extends Feature2D
Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) algorithm by D. Lowe CITE: Lowe04 .

• ### Fields inherited from class org.opencv.core.Algorithm

nativeObj
• ### Constructor Summary

Constructors
Modifier Constructor Description
protected  SIFT​(long addr)
• ### Method Summary

All Methods
Modifier and Type Method Description
static SIFT __fromPtr__​(long addr)
static SIFT create()
(measured in SIFT algorithm as the local contrast) number of octaves is computed automatically from the image resolution.
static SIFT create​(int nfeatures)
static SIFT create​(int nfeatures, int nOctaveLayers)
static SIFT create​(int nfeatures, int nOctaveLayers, double contrastThreshold)
static SIFT create​(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold)
static SIFT create​(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma)
static SIFT create​(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType)
Create SIFT with specified descriptorType.
protected void finalize()
java.lang.String getDefaultName()
Returns the algorithm string identifier.
• ### Methods inherited from class org.opencv.features2d.Feature2D

compute, compute, defaultNorm, descriptorSize, descriptorType, detect, detect, detect, detect, detectAndCompute, detectAndCompute, empty, read, write
• ### Methods inherited from class org.opencv.core.Algorithm

clear, getNativeObjAddr, save
• ### Methods inherited from class java.lang.Object

clone, equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
• ### Constructor Detail

• #### SIFT

protected SIFT​(long addr)
• ### Method Detail

• #### __fromPtr__

public static SIFT __fromPtr__​(long addr)
• #### create

public static SIFT create​(int nfeatures,
int nOctaveLayers,
double contrastThreshold,
double edgeThreshold,
double sigma)
Parameters:
nfeatures - The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers - The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.
contrastThreshold - The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector. Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.
edgeThreshold - The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).
sigma - The sigma of the Gaussian applied to the input image at the octave \#0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.
Returns:
automatically generated
• #### create

public static SIFT create​(int nfeatures,
int nOctaveLayers,
double contrastThreshold,
double edgeThreshold)
Parameters:
nfeatures - The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers - The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.
contrastThreshold - The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector. Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.
edgeThreshold - The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained). is captured with a weak camera with soft lenses, you might want to reduce the number.
Returns:
automatically generated
• #### create

public static SIFT create​(int nfeatures,
int nOctaveLayers,
double contrastThreshold)
Parameters:
nfeatures - The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers - The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.
contrastThreshold - The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector. Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09. is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained). is captured with a weak camera with soft lenses, you might want to reduce the number.
Returns:
automatically generated
• #### create

public static SIFT create​(int nfeatures,
int nOctaveLayers)
Parameters:
nfeatures - The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers - The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution. (low-contrast) regions. The larger the threshold, the less features are produced by the detector. Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09. is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained). is captured with a weak camera with soft lenses, you might want to reduce the number.
Returns:
automatically generated
• #### create

public static SIFT create​(int nfeatures)
Parameters:
nfeatures - The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast) number of octaves is computed automatically from the image resolution. (low-contrast) regions. The larger the threshold, the less features are produced by the detector. Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09. is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained). is captured with a weak camera with soft lenses, you might want to reduce the number.
Returns:
automatically generated
• #### create

public static SIFT create()
(measured in SIFT algorithm as the local contrast) number of octaves is computed automatically from the image resolution. (low-contrast) regions. The larger the threshold, the less features are produced by the detector. Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09. is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained). is captured with a weak camera with soft lenses, you might want to reduce the number.
Returns:
automatically generated
• #### create

public static SIFT create​(int nfeatures,
int nOctaveLayers,
double contrastThreshold,
double edgeThreshold,
double sigma,
int descriptorType)
Create SIFT with specified descriptorType.
Parameters:
nfeatures - The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)
nOctaveLayers - The number of layers in each octave. 3 is the value used in D. Lowe paper. The number of octaves is computed automatically from the image resolution.
contrastThreshold - The contrast threshold used to filter out weak features in semi-uniform (low-contrast) regions. The larger the threshold, the less features are produced by the detector. Note: The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set this argument to 0.09.
edgeThreshold - The threshold used to filter out edge-like features. Note that the its meaning is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are filtered out (more features are retained).
sigma - The sigma of the Gaussian applied to the input image at the octave \#0. If your image is captured with a weak camera with soft lenses, you might want to reduce the number.
descriptorType - The type of descriptors. Only CV_32F and CV_8U are supported.
Returns:
automatically generated
• #### getDefaultName

public java.lang.String getDefaultName()
Description copied from class: Algorithm
Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.
Overrides:
getDefaultName in class Feature2D
Returns:
automatically generated
• #### finalize

protected void finalize()
throws java.lang.Throwable
Overrides:
finalize in class Feature2D
Throws:
java.lang.Throwable