Class for extracting blobs from an image. More...

#include "features2d.hpp"

Inheritance diagram for cv::SimpleBlobDetector:

Collaboration diagram for cv::SimpleBlobDetector:

Classes
struct	Params

Public Member Functions
virtual void	clear ()
	Clears the algorithm state. More...

virtual void	compute (InputArray image, std::vector< KeyPoint > &keypoints, OutputArray descriptors)
	Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant). More...

virtual void	compute (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, OutputArrayOfArrays descriptors)
	This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More...

virtual int	defaultNorm () const

virtual int	descriptorSize () const

virtual int	descriptorType () const

virtual void	detect (InputArray image, std::vector< KeyPoint > &keypoints, InputArray mask=noArray())
	Detects keypoints in an image (first variant) or image set (second variant). More...

virtual void	detect (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, InputArrayOfArrays masks=noArray())
	This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More...

virtual void	detectAndCompute (InputArray image, InputArray mask, std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false)
	Detects keypoints and computes the descriptors. More...

virtual bool	empty () const
	Return true if detector object is empty. More...

virtual String	getDefaultName () const
	Returns the algorithm string identifier. More...

void	read (const String &fileName)

virtual void	read (const FileNode &)
	Reads algorithm parameters from a file storage. More...

virtual void	save (const String &filename) const
	Saves the algorithm to a file. More...

void	write (const String &fileName) const

virtual void	write (FileStorage &) const
	Stores algorithm parameters in a file storage. More...

Static Public Member Functions
static Ptr< SimpleBlobDetector >	create (const SimpleBlobDetector::Params &parameters=SimpleBlobDetector::Params())

template<typename _Tp >
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	Loads algorithm from the file. More...

template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String. More...

Protected Member Functions
void	writeFormat (FileStorage &fs) const

Detailed Description

Class for extracting blobs from an image.

:

The class implements a simple algorithm for extracting blobs from an image:

Convert the source image to binary images by applying thresholding with several thresholds from minThreshold (inclusive) to maxThreshold (exclusive) with distance thresholdStep between neighboring thresholds.
Extract connected components from every binary image by findContours and calculate their centers.
Group centers from several binary images by their coordinates. Close centers form one group that corresponds to one blob, which is controlled by the minDistBetweenBlobs parameter.
From the groups, estimate final centers of blobs and their radiuses and return as locations and sizes of keypoints.

This class performs several filtrations of returned blobs. You should set filterBy* to true/false to turn on/off corresponding filtration. Available filtrations:

By color. This filter compares the intensity of a binary image at the center of a blob to blobColor. If they differ, the blob is filtered out. Use blobColor = 0 to extract dark blobs and blobColor = 255 to extract light blobs.
By area. Extracted blobs have an area between minArea (inclusive) and maxArea (exclusive).
By circularity. Extracted blobs have circularity ( \(\frac{4*\pi*Area}{perimeter * perimeter}\)) between minCircularity (inclusive) and maxCircularity (exclusive).
By ratio of the minimum inertia to maximum inertia. Extracted blobs have this ratio between minInertiaRatio (inclusive) and maxInertiaRatio (exclusive).
By convexity. Extracted blobs have convexity (area / area of blob convex hull) between minConvexity (inclusive) and maxConvexity (exclusive).

Default values of parameters are tuned to extract dark circular blobs.

Member Function Documentation

virtual void cv::Algorithm::clear ( )

inlinevirtualinherited

Clears the algorithm state.

Reimplemented in cv::FlannBasedMatcher, cv::DescriptorMatcher, and cv::cuda::DescriptorMatcher.

virtual void cv::Feature2D::compute	(	InputArray	image,
		std::vector< KeyPoint > &	keypoints,
		OutputArray	descriptors
	)

virtualinherited

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

Parameters

image	Image.
keypoints	Input collection of keypoints. Keypoints for which a descriptor cannot be computed are removed. Sometimes new keypoints can be added, for example: SIFT duplicates keypoint with several dominant orientations (for each orientation).
descriptors	Computed descriptors. In the second variant of the method descriptors[i] are descriptors computed for a keypoints[i]. Row j is the keypoints (or keypoints[i]) is the descriptor for keypoint j-th keypoint.

virtual void cv::Feature2D::compute	(	InputArrayOfArrays	images,
		std::vector< std::vector< KeyPoint > > &	keypoints,
		OutputArrayOfArrays	descriptors
	)

virtualinherited

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Parameters

images	Image set.
keypoints	Input collection of keypoints. Keypoints for which a descriptor cannot be computed are removed. Sometimes new keypoints can be added, for example: SIFT duplicates keypoint with several dominant orientations (for each orientation).
descriptors	Computed descriptors. In the second variant of the method descriptors[i] are descriptors computed for a keypoints[i]. Row j is the keypoints (or keypoints[i]) is the descriptor for keypoint j-th keypoint.

static Ptr<SimpleBlobDetector> cv::SimpleBlobDetector::create ( const SimpleBlobDetector::Params & parameters = SimpleBlobDetector::Params() )

static

virtual int cv::Feature2D::defaultNorm ( ) const

virtualinherited

virtual int cv::Feature2D::descriptorSize ( ) const

virtualinherited

virtual int cv::Feature2D::descriptorType ( ) const

virtualinherited

virtual void cv::Feature2D::detect	(	InputArray	image,
		std::vector< KeyPoint > &	keypoints,
		InputArray	mask = `noArray()`
	)

virtualinherited

Detects keypoints in an image (first variant) or image set (second variant).

Parameters

image	Image.
keypoints	The detected keypoints. In the second variant of the method keypoints[i] is a set of keypoints detected in images[i] .
mask	Mask specifying where to look for keypoints (optional). It must be a 8-bit integer matrix with non-zero values in the region of interest.

Reimplemented in cv::AgastFeatureDetector_Impl.

virtual void cv::Feature2D::detect	(	InputArrayOfArrays	images,
		std::vector< std::vector< KeyPoint > > &	keypoints,
		InputArrayOfArrays	masks = `noArray()`
	)

virtualinherited

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Parameters

images	Image set.
keypoints	The detected keypoints. In the second variant of the method keypoints[i] is a set of keypoints detected in images[i] .
masks	Masks for each input image specifying where to look for keypoints (optional). masks[i] is a mask for images[i].

virtual void cv::Feature2D::detectAndCompute	(	InputArray	image,
		InputArray	mask,
		std::vector< KeyPoint > &	keypoints,
		OutputArray	descriptors,
		bool	useProvidedKeypoints = `false`
	)

virtualinherited

Detects keypoints and computes the descriptors.

virtual bool cv::Feature2D::empty ( ) const

virtualinherited

Return true if detector object is empty.

Reimplemented from cv::Algorithm.

virtual String cv::Algorithm::getDefaultName ( ) const

virtualinherited

Returns the algorithm string identifier.

This string is used as top level xml/yml node tag when the object is saved to a file or string.

template<typename _Tp >

static Ptr<_Tp> cv::Algorithm::load	(	const String &	filename,
		const String &	objname = `String()`
	)

inlinestaticinherited

Loads algorithm from the file.

Parameters

filename	Name of the file to read.
objname	The optional name of the node to read (if empty, the first top-level node will be used)

This is static template method of Algorithm. It's usage is following (in the case of SVM):

Ptr<SVM> svm = Algorithm::load<SVM>("my_svm_model.xml");

In order to make this method work, the derived class must overwrite Algorithm::read(const FileNode& fn).

References cv::Ptr< T >::empty(), cv::FileNode::empty(), cv::FileStorage::getFirstTopLevelNode(), and cv::FileStorage::READ.

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template<typename _Tp >

static Ptr<_Tp> cv::Algorithm::loadFromString	(	const String &	strModel,
		const String &	objname = `String()`
	)

inlinestaticinherited

Loads algorithm from a String.

Parameters

strModel	The string variable containing the model you want to load.
objname	The optional name of the node to read (if empty, the first top-level node will be used)

This is static template method of Algorithm. It's usage is following (in the case of SVM):

Ptr<SVM> svm = Algorithm::loadFromString<SVM>(myStringModel);

References CV_WRAP, cv::Ptr< T >::empty(), cv::FileNode::empty(), cv::FileStorage::getFirstTopLevelNode(), cv::FileStorage::MEMORY, and cv::FileStorage::READ.

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void cv::Feature2D::read ( const String & fileName )

inherited

virtual void cv::Feature2D::read ( const FileNode & fn )

virtualinherited

Reads algorithm parameters from a file storage.

Reimplemented from cv::Algorithm.

virtual void cv::Algorithm::save ( const String & filename ) const

virtualinherited

Saves the algorithm to a file.

In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

void cv::Feature2D::write ( const String & fileName ) const

inherited

virtual void cv::Feature2D::write ( FileStorage & fs ) const

virtualinherited

Stores algorithm parameters in a file storage.

Reimplemented from cv::Algorithm.

void cv::Algorithm::writeFormat ( FileStorage & fs ) const

protectedinherited

The documentation for this class was generated from the following file:

features2d/include/opencv2/features2d.hpp

Classes

Public Member Functions

Static Public Member Functions

Protected Member Functions

Detailed Description

Member Function Documentation