SIFT

Objective-C

@interface SIFT : Feature2D

Swift

class SIFT : Feature2D

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

Member of Features2d

Methods

  • Declaration

    Objective-C

    + (nonnull SIFT *)create:(int)nfeatures
           nOctaveLayers:(int)nOctaveLayers
       contrastThreshold:(double)contrastThreshold
           edgeThreshold:(double)edgeThreshold
                   sigma:(double)sigma;

    Swift

    class func create(nfeatures: Int32, nOctaveLayers: Int32, contrastThreshold: Double, edgeThreshold: Double, sigma: Double) -> SIFT

    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.

  • Declaration

    Objective-C

    + (nonnull SIFT *)create:(int)nfeatures
           nOctaveLayers:(int)nOctaveLayers
       contrastThreshold:(double)contrastThreshold
           edgeThreshold:(double)edgeThreshold;

    Swift

    class func create(nfeatures: Int32, nOctaveLayers: Int32, contrastThreshold: Double, edgeThreshold: Double) -> SIFT

    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.

  • Declaration

    Objective-C

    + (nonnull SIFT *)create:(int)nfeatures
           nOctaveLayers:(int)nOctaveLayers
       contrastThreshold:(double)contrastThreshold;

    Swift

    class func create(nfeatures: Int32, nOctaveLayers: Int32, contrastThreshold: Double) -> SIFT

    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.

  • Declaration

    Objective-C

    + (nonnull SIFT *)create:(int)nfeatures nOctaveLayers:(int)nOctaveLayers;

    Swift

    class func create(nfeatures: Int32, nOctaveLayers: Int32) -> SIFT

    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.

  • Declaration

    Objective-C

    + (nonnull SIFT *)create:(int)nfeatures;

    Swift

    class func create(nfeatures: Int32) -> SIFT

    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.

    		 
  •  (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.

    Declaration

    Objective-C

    + (nonnull SIFT *)create;

    Swift

    class func create() -> SIFT

  • Declaration

    Objective-C

    - (nonnull NSString *)getDefaultName;

    Swift

    func getDefaultName() -> String