CvHaarClassifierCascade.HaarDetectObjects Method (CvArr, CvMemStorage, Double, Int32)

CvHaarClassifierCascadeHaarDetectObjects Method (CvArr, CvMemStorage, Double, Int32)

OpenCvSharp Class Library

Finds rectangular regions in the given image that are likely to contain objects the cascade has been trained for and returns those regions as a sequence of rectangles.

Namespace: OpenCvSharp
Assembly: OpenCvSharp (in OpenCvSharp.dll) Version: 1.0.0.0 (1.0.0.0)

Syntax

C++

Copy

public CvSeq HaarDetectObjects(
	CvArr image,
	CvMemStorage storage,
	double scaleFactor,
	int minNeighbors
)

Public Function HaarDetectObjects ( 
	image As CvArr,
	storage As CvMemStorage,
	scaleFactor As Double,
	minNeighbors As Integer
) As CvSeq

public:
CvSeq^ HaarDetectObjects(
	CvArr^ image, 
	CvMemStorage^ storage, 
	double scaleFactor, 
	int minNeighbors
)

member HaarDetectObjects : 
        image : CvArr * 
        storage : CvMemStorage * 
        scaleFactor : float * 
        minNeighbors : int -> CvSeq

Parameters

image: Type: OpenCvSharpCvArr
Image to detect objects in.
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.

Return Value

Type: CvSeq

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

Reference

CvHaarClassifierCascade Class

HaarDetectObjects Overload

OpenCvSharp Namespace