public CvSeq<CvAvgComp> HaarDetectObjects(
	CvHaarClassifierCascade cascade,
	CvMemStorage storage,
	double scaleFactor,
	int minNeighbors,
	HaarDetectionType flags,
	CvSize minSize,
	CvSize maxSize
)

Public Function HaarDetectObjects ( 
	cascade As CvHaarClassifierCascade,
	storage As CvMemStorage,
	scaleFactor As Double,
	minNeighbors As Integer,
	flags As HaarDetectionType,
	minSize As CvSize,
	maxSize As CvSize
) As CvSeq(Of CvAvgComp)

public:
CvSeq<CvAvgComp>^ HaarDetectObjects(
	CvHaarClassifierCascade^ cascade, 
	CvMemStorage^ storage, 
	double scaleFactor, 
	int minNeighbors, 
	HaarDetectionType flags, 
	CvSize minSize, 
	CvSize maxSize
)

member HaarDetectObjects : 
        cascade : CvHaarClassifierCascade * 
        storage : CvMemStorage * 
        scaleFactor : float * 
        minNeighbors : int * 
        flags : HaarDetectionType * 
        minSize : CvSize * 
        maxSize : CvSize -> CvSeq<CvAvgComp> 

Parameters

cascade

Type: OpenCvSharpCvHaarClassifierCascade
Haar classifier cascade in internal representation.

storage

Type: OpenCvSharpCvMemStorage
Memory storage to store the resultant sequence of the object candidate rectangles.

scaleFactor

Type: SystemDouble
The factor by which the search window is scaled between the subsequent scans, for example, 1.1 means increasing window by 10%.

minNeighbors

Type: SystemInt32
Minimum number (minus 1) of neighbor rectangles that makes up an object. All the groups of a smaller number of rectangles than min_neighbors-1 are rejected. If min_neighbors is 0, the function does not any grouping at all and returns all the detected candidate rectangles, which may be useful if the user wants to apply a customized grouping procedure.

flags

Type: OpenCvSharpHaarDetectionType
Mode of operation. Currently the only flag that may be specified is CV_HAAR_DO_CANNY_PRUNING. If it is set, the function uses Canny edge detector to reject some image regions that contain too few or too much edges and thus can not contain the searched object. The particular threshold values are tuned for face detection and in this case the pruning speeds up the processing.

minSize

Type: OpenCvSharpCvSize
Minimum window size. By default, it is set to the size of samples the classifier has been trained on (~20×20 for face detection).

maxSize

Type: OpenCvSharpCvSize
Maximum window size.

Return Value

[Missing <returns> documentation for "M:OpenCvSharp.CvArr.HaarDetectObjects(OpenCvSharp.CvHaarClassifierCascade,OpenCvSharp.CvMemStorage,System.Double,System.Int32,OpenCvSharp.HaarDetectionType,OpenCvSharp.CvSize,OpenCvSharp.CvSize)"]

Reference