cv::SimpleBlobDetector Class Reference

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

#include <opencv2/features2d.hpp>

Collaboration diagram for cv::SimpleBlobDetector:

Classes
struct	Params

Public Member Functions
virtual const std::vector< std::vector< cv::Point > > &	getBlobContours () const
virtual String	getDefaultName () const CV_OVERRIDE
virtual SimpleBlobDetector::Params	getParams () const =0
virtual void	setParams (const SimpleBlobDetector::Params &params)=0
Public Member Functions inherited from cv::Feature2D
virtual	~Feature2D ()
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).
virtual void	compute (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, OutputArrayOfArrays descriptors)
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).
virtual void	detect (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, InputArrayOfArrays masks=noArray())
virtual void	detectAndCompute (InputArray image, InputArray mask, std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false)
virtual bool	empty () const CV_OVERRIDE
	Return true if detector object is empty.
virtual void	read (const FileNode &) CV_OVERRIDE
	Reads algorithm parameters from a file storage.
void	read (const String &fileName)
void	write (const Ptr< FileStorage > &fs, const String &name) const
void	write (const String &fileName) const
virtual void	write (FileStorage &) const CV_OVERRIDE
	Stores algorithm parameters in a file storage.
void	write (FileStorage &fs, const String &name) const
Public Member Functions inherited from cv::Algorithm
	Algorithm ()
virtual	~Algorithm ()
virtual void	clear ()
	Clears the algorithm state.
virtual void	save (const String &filename) const
void	write (const Ptr< FileStorage > &fs, const String &name=String()) const
void	write (FileStorage &fs, const String &name) const

Static Public Member Functions
static Ptr< SimpleBlobDetector >	create (const SimpleBlobDetector::Params &parameters=SimpleBlobDetector::Params())
Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	Loads algorithm from the file.
template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String.
template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node.

Additional Inherited Members
Protected Member Functions inherited from cv::Algorithm
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:

1. 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.
2. Extract connected components from every binary image by findContours and calculate their centers.
3. 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.
4. 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

create()

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

static

Python:
	cv.SimpleBlobDetector.create(	[, parameters]	) ->	retval
	cv.SimpleBlobDetector_create(	[, parameters]	) ->	retval

getBlobContours()

virtual const std::vector< std::vector< cv::Point > > & cv::SimpleBlobDetector::getBlobContours ( ) const

virtual

Python:
	cv.SimpleBlobDetector.getBlobContours(		) ->	retval

getDefaultName()

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

virtual

Python:
	cv.SimpleBlobDetector.getDefaultName(		) ->	retval

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.

Reimplemented from cv::Feature2D.

getParams()

virtual SimpleBlobDetector::Params cv::SimpleBlobDetector::getParams ( ) const

pure virtual

Python:
	cv.SimpleBlobDetector.getParams(		) ->	retval

setParams()

virtual void cv::SimpleBlobDetector::setParams ( const SimpleBlobDetector::Params &  params )

pure virtual

Python:
	cv.SimpleBlobDetector.setParams(	params	) ->	None

---

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

• opencv2/features2d.hpp