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cvDetectFeature2D_SIFT

Basic

Extracting keypoints and computing descriptors using the Scale Invariant Feature Transform (SIFT) algorithm.

	Name	Type	Range	Description
	inImage	Image		Input image
	inMask	Region*
	inFeatures	Integer	0 -	The number of best features to retain. The features are ranked by their scores (measured in SIFT algorithm as the local contrast).
	inOctaveLayers	Integer	1 -	The number of layers in each octave. The number of octaves is computed automatically from the image resolution.
	inContrastThreshold	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.
	inEdgeThreshold	Double		The threshold used to filter out edge-like features.
	inSigma	Double		The sigma of the Gaussian applied to the input image at the octave.
	outKeyPoints	AnnotatedPoint2DArray		Annotated x value mean class id and y mean angle
	outDescriptors	Matrix		Matrix contained features values and class id.

Complexity Level