java.lang.Object
- org.opencv.core.Algorithm
- - org.opencv.features2d.Feature2D
  - - org.opencv.features2d.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 .

Field Summary
- Fields inherited from class org.opencv.core.Algorithm
  nativeObj

Constructor Summary

Constructors
Modifier Constructor Description

protected SIFT(long addr)

Method Summary

All Methods Static Methods Instance Methods Concrete 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

Class SIFT

Field Summary

Fields inherited from class org.opencv.core.Algorithm

Constructor Summary

Method Summary

Methods inherited from class org.opencv.features2d.Feature2D

Methods inherited from class org.opencv.core.Algorithm

Methods inherited from class java.lang.Object

Constructor Detail

SIFT

Method Detail

__fromPtr__

create

create

create

create

create

create

create

getDefaultName

finalize

fromPtr