Class cv::MSER#

Maximally stable extremal region extractor. View details

#include <opencv2/features.hpp>

Collaboration diagram for cv::MSER:

Public Member Functions#

Public Member Functions inherited from cv::Feature2D

Return	Name	Description
	`~Feature2D()`
`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).
`void`	`compute(` `InputArrayOfArrays images,` `std::vector< std::vector< KeyPoint > > & keypoints,` `OutputArrayOfArrays descriptors )`
`int`	`defaultNorm()`
`int`	`descriptorSize()`
`int`	`descriptorType()`
`void`	`detect(` `InputArray image,` `std::vector< KeyPoint > & keypoints,` `InputArray mask = noArray() )`	Detects keypoints in an image (first variant) or image set (second variant).
`void`	`detect(` `InputArrayOfArrays images,` `std::vector< std::vector< KeyPoint > > & keypoints,` `InputArrayOfArrays masks = noArray() )`
`void`	`detectAndCompute(` `InputArray image,` `InputArray mask,` `std::vector< KeyPoint > & keypoints,` `OutputArray descriptors,` `bool useProvidedKeypoints = false )`
`bool`	`empty()`	Return true if detector object is empty.
`String`	`getDefaultName()`
`void`	`read(const FileNode & fn)`	Reads algorithm parameters from a file storage.
`void`	`read(const String & fileName)`
`void`	`write(const String & fileName)`
`void`	`write(FileStorage & fs)`	Stores algorithm parameters in a file storage.
`void`	`write(` `FileStorage & fs,` `const String & name )`

Public Member Functions inherited from cv::Algorithm

Return	Name	Description
	`Algorithm()`
	`~Algorithm()`
`void`	`clear()`	Clears the algorithm state.
`bool`	`empty()`	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
`String`	`getDefaultName()`
`void`	`read(const FileNode & fn)`	Reads algorithm parameters from a file storage.
`void`	`save(const String & filename)`
`void`	`write(` `const Ptr< FileStorage > & fs,` `const String & name = String() )`
`void`	`write(FileStorage & fs)`	Stores algorithm parameters in a file storage.
`void`	`write(` `FileStorage & fs,` `const String & name )`

Static Public Member Functions#

Static Public Member Functions inherited from cv::Algorithm

Return	Name	Description
`static Ptr< _Tp >`	`load(` `const String & filename,` `const String & objname = String() )`	Loads algorithm from the file.
`static Ptr< _Tp >`	`loadFromString(` `const String & strModel,` `const String & objname = String() )`	Loads algorithm from a String.
`static Ptr< _Tp >`	`read(const FileNode & fn)`	Reads algorithm from the file node.

Additional Inherited Members#

Detailed Description#

Maximally stable extremal region extractor.

The class encapsulates all the parameters of the MSER extraction algorithm (see wiki article).

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

Examples: samples/python/snippets/mser.py.

Member Function Documentation#

create()#

static Ptr< MSER > cv::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 )

Python:

cv.MSER.create([, delta[, min_area[, max_area[, max_variation[, min_diversity[, max_evolution[, area_threshold[, min_margin[, edge_blur_size]]]]]]]]]) -> retval

cv.MSER_create([, delta[, min_area[, max_area[, max_variation[, min_diversity[, max_evolution[, area_threshold[, min_margin[, edge_blur_size]]]]]]]]]) -> retval

Full constructor 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 similar 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

detectRegions()#

void cv::MSER::detectRegions(
InputArray image,
std::vector< std::vector< Point > > & msers,
std::vector< Rect > & bboxes )

Python:

cv.MSER.detectRegions(image) -> msers, bboxes

Detect MSER regions.

Parameters

image — input image (8UC1, 8UC3 or 8UC4, must be greater or equal than 3x3)
msers — resulting list of point sets
bboxes — resulting bounding boxes

getAreaThreshold()#

double cv::MSER::getAreaThreshold()

Python:

cv.MSER.getAreaThreshold() -> retval

getDefaultName()#

String cv::MSER::getDefaultName()

Python:

cv.MSER.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.

getDelta()#

int cv::MSER::getDelta()

Python:

cv.MSER.getDelta() -> retval

getEdgeBlurSize()#

int cv::MSER::getEdgeBlurSize()

Python:

cv.MSER.getEdgeBlurSize() -> retval

getMaxArea()#

int cv::MSER::getMaxArea()

Python:

cv.MSER.getMaxArea() -> retval

getMaxEvolution()#

int cv::MSER::getMaxEvolution()

Python:

cv.MSER.getMaxEvolution() -> retval

getMaxVariation()#

double cv::MSER::getMaxVariation()

Python:

cv.MSER.getMaxVariation() -> retval

getMinArea()#

int cv::MSER::getMinArea()

Python:

cv.MSER.getMinArea() -> retval

getMinDiversity()#

double cv::MSER::getMinDiversity()

Python:

cv.MSER.getMinDiversity() -> retval

getMinMargin()#

double cv::MSER::getMinMargin()

Python:

cv.MSER.getMinMargin() -> retval

getPass2Only()#

bool cv::MSER::getPass2Only()

Python:

cv.MSER.getPass2Only() -> retval

setAreaThreshold()#

void cv::MSER::setAreaThreshold(double areaThreshold)

Python:

cv.MSER.setAreaThreshold(areaThreshold)

setDelta()#

void cv::MSER::setDelta(int delta)

Python:

cv.MSER.setDelta(delta)

setEdgeBlurSize()#

void cv::MSER::setEdgeBlurSize(int edge_blur_size)

Python:

cv.MSER.setEdgeBlurSize(edge_blur_size)

setMaxArea()#

void cv::MSER::setMaxArea(int maxArea)

Python:

cv.MSER.setMaxArea(maxArea)

setMaxEvolution()#

void cv::MSER::setMaxEvolution(int maxEvolution)

Python:

cv.MSER.setMaxEvolution(maxEvolution)

setMaxVariation()#

void cv::MSER::setMaxVariation(double maxVariation)

Python:

cv.MSER.setMaxVariation(maxVariation)

setMinArea()#

void cv::MSER::setMinArea(int minArea)

Python:

cv.MSER.setMinArea(minArea)

setMinDiversity()#

void cv::MSER::setMinDiversity(double minDiversity)

Python:

cv.MSER.setMinDiversity(minDiversity)

setMinMargin()#

void cv::MSER::setMinMargin(double min_margin)

Python:

cv.MSER.setMinMargin(min_margin)

setPass2Only()#

void cv::MSER::setPass2Only(bool f)

Python:

cv.MSER.setPass2Only(f)

Source file#

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

opencv2/features.hpp