Class cv::SimpleBlobDetector#

Class for extracting blobs from an image. : View details

#include <opencv2/features.hpp>

Collaboration diagram for cv::SimpleBlobDetector:

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#

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#

create()#

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

Python:

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

cv.SimpleBlobDetector_create([, parameters]) -> retval

getBlobContours()#

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

Python:

cv.SimpleBlobDetector.getBlobContours() -> retval

Returns the contours of the blobs detected during the last call to detect().

Note

The Params::collectContours parameter must be set to true before calling detect() for this method to return any data.

getDefaultName()#

String cv::SimpleBlobDetector::getDefaultName()

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.

getParams()#

SimpleBlobDetector::Params cv::SimpleBlobDetector::getParams()

Python:

cv.SimpleBlobDetector.getParams() -> retval

setParams()#

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

Python:

cv.SimpleBlobDetector.setParams(params)

Source file#

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

opencv2/features.hpp