cv::SimpleBlobDetector Class Reference
2D 特征框架 » 特征检测和描述

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

#include <opencv2/features2d.hpp>

Inheritance diagram for cv::SimpleBlobDetector:
cv::Feature2D cv::Algorithm

struct Params

Public Member Functions

virtual 字符串 getDefaultName () const CV_OVERRIDE
- 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). 更多...
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). 更多...
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. 更多...
void read (const 字符串 &fileName)
virtual void read (const FileNode &) CV_OVERRIDE
Reads algorithm parameters from a file storage. 更多...
void write (const 字符串 &fileName) const
virtual void write ( FileStorage &) const CV_OVERRIDE
Stores algorithm parameters in a file storage. 更多...
void write (const Ptr < FileStorage > &fs, const 字符串 &name= 字符串 ()) const
- Public Member Functions inherited from cv::Algorithm
Algorithm ()
virtual ~Algorithm ()
virtual void clear ()
Clears the algorithm state. 更多...
virtual void save (const 字符串 &filename) const
void write (const Ptr < FileStorage > &fs, const 字符串 &name= 字符串 ()) const
simplified API for language bindings This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. 更多...

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 字符串 &filename, const 字符串 &objname= 字符串 ())
Loads algorithm from the file. 更多...
template<typename _Tp >
static Ptr < _Tp > loadFromString (const 字符串 &strModel, const 字符串 &objname= 字符串 ())
Loads algorithm from a String. 更多...
template<typename _Tp >
static Ptr < _Tp > read (const FileNode &fn)
Reads algorithm from the file node. 更多...

额外继承成员

- Protected Member Functions inherited from cv::Algorithm
void writeFormat ( FileStorage &fs) const

详细描述

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.

成员函数文档编制

create()

static Ptr < SimpleBlobDetector > cv::SimpleBlobDetector::create ( const SimpleBlobDetector::Params & 参数 = SimpleBlobDetector::Params () )
static
Python:
retval = cv.SimpleBlobDetector_create( [, parameters] )

getDefaultName()

virtual 字符串 cv::SimpleBlobDetector::getDefaultName ( ) const
virtual
Python:
retval = cv.SimpleBlobDetector.getDefaultName( )

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 .


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