Class SIFT

Namespace

OpenCvSharp.Features2D

Assembly

OpenCvSharp.dll

SIFT implementation.

public class SIFT : Feature2D, IDisposable, ICvPtrHolder

Inheritance

object

DisposableObject

DisposableCvObject

Algorithm

Feature2D

SIFT

Implements

IDisposable

ICvPtrHolder

Inherited Members

Feature2D.DescriptorSize

Feature2D.DescriptorType

Feature2D.DefaultNorm

Feature2D.Empty()

Feature2D.Detect(Mat, Mat)

Feature2D.Detect(InputArray, Mat)

Feature2D.Detect(IEnumerable<Mat>, IEnumerable<Mat>)

Feature2D.Compute(InputArray, ref KeyPoint[], OutputArray)

Feature2D.Compute(IEnumerable<Mat>, ref KeyPoint[][], IEnumerable<Mat>)

Feature2D.DetectAndCompute(InputArray, InputArray, out KeyPoint[], OutputArray, bool)

Feature2D.Write(string)

Feature2D.Read(string)

Feature2D.GetDefaultName()

Algorithm.Write(FileStorage)

Algorithm.Read(FileNode)

Algorithm.Save(string)

DisposableCvObject.ptr

DisposableCvObject.DisposeUnmanaged()

DisposableCvObject.CvPtr

DisposableObject.DataHandle

DisposableObject.IsDisposed

DisposableObject.IsEnabledDispose

DisposableObject.AllocatedMemory

DisposableObject.AllocatedMemorySize

DisposableObject.Dispose()

DisposableObject.Dispose(bool)

DisposableObject.AllocGCHandle(object)

DisposableObject.AllocMemory(int)

DisposableObject.NotifyMemoryPressure(long)

DisposableObject.ThrowIfDisposed()

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Constructors

SIFT(nint)

Creates instance by raw pointer cv::SIFT*

protected SIFT(nint p)

Parameters

p nint

Methods

Create(int, int, double, double, double)

The SIFT constructor.

public static SIFT Create(int nFeatures = 0, int nOctaveLayers = 3, double contrastThreshold = 0.04, double edgeThreshold = 10, double sigma = 1.6)

Parameters

nFeatures int

The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast)

nOctaveLayers int

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 double

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.

edgeThreshold double

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 double

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

SIFT

DisposeManaged()

Releases managed resources

protected override void DisposeManaged()