public static Point2f[] GoodFeaturesToTrack(
	InputArray src,
	int maxCorners,
	double qualityLevel,
	double minDistance,
	InputArray mask,
	int blockSize,
	bool useHarrisDetector,
	double k
)

Public Shared Function GoodFeaturesToTrack ( 
	src As InputArray,
	maxCorners As Integer,
	qualityLevel As Double,
	minDistance As Double,
	mask As InputArray,
	blockSize As Integer,
	useHarrisDetector As Boolean,
	k As Double
) As Point2f()

public:
static array<Point2f>^ GoodFeaturesToTrack(
	InputArray^ src, 
	int maxCorners, 
	double qualityLevel, 
	double minDistance, 
	InputArray^ mask, 
	int blockSize, 
	bool useHarrisDetector, 
	double k
)

static member GoodFeaturesToTrack : 
        src : InputArray * 
        maxCorners : int * 
        qualityLevel : float * 
        minDistance : float * 
        mask : InputArray * 
        blockSize : int * 
        useHarrisDetector : bool * 
        k : float -> Point2f[] 

Parameters

src

Type: OpenCvSharp.CPlusPlusInputArray
Input 8-bit or floating-point 32-bit, single-channel image.

maxCorners

Type: SystemInt32
Maximum number of corners to return. If there are more corners than are found, the strongest of them is returned.

qualityLevel

Type: SystemDouble
Parameter characterizing the minimal accepted quality of image corners. The parameter value is multiplied by the best corner quality measure, which is the minimal eigenvalue or the Harris function response (see cornerHarris() ). The corners with the quality measure less than the product are rejected. For example, if the best corner has the quality measure = 1500, and the qualityLevel=0.01, then all the corners with the quality measure less than 15 are rejected.

minDistance

Type: SystemDouble
Minimum possible Euclidean distance between the returned corners.

mask

Type: OpenCvSharp.CPlusPlusInputArray
Optional region of interest. If the image is not empty (it needs to have the type CV_8UC1 and the same size as image ), it specifies the region in which the corners are detected.

blockSize

Type: SystemInt32
Size of an average block for computing a derivative covariation matrix over each pixel neighborhood.

useHarrisDetector

Type: SystemBoolean
Parameter indicating whether to use a Harris detector

k

Type: SystemDouble
Free parameter of the Harris detector.

Return Value

Reference