Maximally stable extremal region extractor. More...

#include <features2d.hpp>

Public Member Functions
virtual CV_WRAP void	detectRegions (InputArray image, CV_OUT std::vector< std::vector< Point > > &msers, std::vector< Rect > &bboxes)=0
	Detect MSER regions.
virtual CV_WRAP void	detect (InputArray image, CV_OUT 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())
	This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
virtual CV_WRAP void	compute (InputArray image, CV_OUT CV_IN_OUT 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)
	This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
virtual CV_WRAP void	detectAndCompute (InputArray image, InputArray mask, CV_OUT std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false)
	Detects keypoints and computes the descriptors.
virtual CV_WRAP bool	empty () const
	Return true if detector object is empty.
virtual CV_WRAP void	clear ()
	Clears the algorithm state.
virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage.
virtual void	read (const FileNode &fn)
	Reads algorithm parameters from a file storage.
virtual CV_WRAP void	save (const String &filename) const
	Saves the algorithm to a file.
virtual CV_WRAP String	getDefaultName () const
	Returns the algorithm string identifier.
Static Public Member Functions
static CV_WRAP Ptr< MSER >	create (int _delta=5, int _min_area=60, int _max_area=14400, double _max_variation=0.25, double _min_diversity=.2, int _max_evolution=200, double _area_threshold=1.01, double _min_margin=0.003, int _edge_blur_size=5)
	Full consturctor for MSER detector.
template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node.
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.

Detailed Description

Maximally stable extremal region extractor.

The class encapsulates all the parameters of the MSER extraction algorithm (see [wiki article](http://en.wikipedia.org/wiki/Maximally_stable_extremal_regions)).

there are two different implementation of MSER: one for grey image, one for color image

the grey image algorithm is taken from: nister2008linear ; the paper claims to be faster than union-find method; it actually get 1.5~2m/s on my centrino L7200 1.2GHz laptop.

the color image algorithm is taken from: forssen2007maximally ; it should be much slower than grey image method ( 3~4 times ); the chi_table.h file is taken directly from paper's source code which is distributed under GPL.

(Python) A complete example showing the use of the MSER detector can be found at samples/python/mser.py

Definition at line 336 of file features2d.hpp.

Member Function Documentation

virtual CV_WRAP void clear ( ) [virtual, inherited]

Clears the algorithm state.

Reimplemented in DescriptorMatcher, and FlannBasedMatcher.

Definition at line 2984 of file core.hpp.

virtual CV_WRAP void compute	(	InputArray	image,
		CV_OUT CV_IN_OUT std::vector< KeyPoint > &	keypoints,
		OutputArray	descriptors
	)		`[virtual, inherited]`

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 compute	(	InputArrayOfArrays	images,
		std::vector< std::vector< KeyPoint > > &	keypoints,
		OutputArrayOfArrays	descriptors
	)		`[virtual, inherited]`

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 CV_WRAP Ptr<MSER> create	(	int	_delta = `5`,
		int	_min_area = `60`,
		int	_max_area = `14400`,
		double	_max_variation = `0.25`,
		double	_min_diversity = `.2`,
		int	_max_evolution = `200`,
		double	_area_threshold = `1.01`,
		double	_min_margin = `0.003`,
		int	_edge_blur_size = `5`
	)		`[static]`

Full consturctor for MSER detector.

Parameters:

_delta	it compares $(size_{i}-size_{i-delta})/size_{i-delta}$
_min_area	prune the area which smaller than minArea
_max_area	prune the area which bigger than maxArea
_max_variation	prune the area have simliar size to its children
_min_diversity	for color image, trace back to cut off mser with diversity less than min_diversity
_max_evolution	for color image, the evolution steps
_area_threshold	for color image, the area threshold to cause re-initialize
_min_margin	for color image, ignore too small margin
_edge_blur_size	for color image, the aperture size for edge blur

virtual CV_WRAP void detect	(	InputArray	image,
		CV_OUT std::vector< KeyPoint > &	keypoints,
		InputArray	mask = `noArray()`
	)		`[virtual, inherited]`

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.

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

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 CV_WRAP void detectAndCompute	(	InputArray	image,
		InputArray	mask,
		CV_OUT std::vector< KeyPoint > &	keypoints,
		OutputArray	descriptors,
		bool	useProvidedKeypoints = `false`
	)		`[virtual, inherited]`

Detects keypoints and computes the descriptors.

virtual CV_WRAP void detectRegions	(	InputArray	image,
		CV_OUT std::vector< std::vector< Point > > &	msers,
		std::vector< Rect > &	bboxes
	)		`[pure virtual]`

Detect MSER regions.

Parameters:

image	input image (8UC1, 8UC3 or 8UC4)
msers	resulting list of point sets
bboxes	resulting bounding boxes

virtual CV_WRAP bool empty ( ) const [virtual, inherited]

Return true if detector object is empty.

Reimplemented from Algorithm.

virtual CV_WRAP String getDefaultName ( ) const [virtual, inherited]

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.

static Ptr<_Tp> load	(	const String &	filename,
		const String &	objname = `String()`
	)		`[static, inherited]`

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).

Definition at line 3027 of file core.hpp.

static Ptr<_Tp> loadFromString	(	const String &	strModel,
		const String &	objname = `String()`
	)		`[static, inherited]`

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);

Definition at line 3046 of file core.hpp.

static Ptr<_Tp> read ( const FileNode & fn ) [static, inherited]

Reads algorithm from the file node.

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

     Ptr<SVM> svm = Algorithm::read<SVM>(fn);

In order to make this method work, the derived class must overwrite Algorithm::read(const FileNode& fn) and also have static create() method without parameters (or with all the optional parameters)

Reimplemented in DescriptorMatcher, and FlannBasedMatcher.

Definition at line 3008 of file core.hpp.

virtual void read ( const FileNode & fn ) [virtual, inherited]

Reads algorithm parameters from a file storage.

Reimplemented in DescriptorMatcher, and FlannBasedMatcher.

Definition at line 2992 of file core.hpp.

virtual CV_WRAP void save ( const String & filename ) const [virtual, inherited]

Saves the algorithm to a file.

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

virtual void write ( FileStorage & fs ) const [virtual, inherited]

Stores algorithm parameters in a file storage.

Reimplemented in DescriptorMatcher, and FlannBasedMatcher.

Definition at line 2988 of file core.hpp.

Type:	Program
Mbed OS support:	Mbed 2 deprecated
Created:	31 Mar 2016
Imports:	152
Forks:	0
Commits:	1
Dependents:	0
Dependencies:	1
Followers:	2

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MSER Class Reference [Feature Detection and Description]

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MSER Class Reference
[Feature Detection and Description]