OpenCV  4.0.0-rc
Open Source Computer Vision
Public Member Functions | Public Attributes | List of all members

The ERStat structure represents a class-specific Extremal Region (ER). More...

#include "erfilter.hpp"

Public Member Functions

 ERStat (int level=256, int pixel=0, int x=0, int y=0)
 Constructor. More...
 
 ~ERStat ()
 Destructor. More...
 

Public Attributes

int area
 incrementally computable features More...
 
double central_moments [3]
 order 2 central moments to construct the covariance matrix More...
 
ERStatchild
 
float convex_hull_ratio
 
Ptr< std::deque< int > > crossings
 horizontal crossings More...
 
int euler
 Euler's number. More...
 
float hole_area_ratio
 2nd stage features More...
 
int level
 
bool local_maxima
 whenever the regions is a local maxima of the probability More...
 
ERStatmax_probability_ancestor
 
float med_crossings
 median of the crossings at three different height levels More...
 
ERStatmin_probability_ancestor
 
ERStatnext
 
float num_inflexion_points
 
ERStatparent
 pointers preserving the tree structure of the component tree More...
 
int perimeter
 
int pixel
 seed point and the threshold (max grey-level value) More...
 
std::vector< int > * pixels
 
ERStatprev
 
double probability
 probability that the ER belongs to the class we are looking for More...
 
double raw_moments [2]
 order 1 raw moments to derive the centroid More...
 
Rect rect
 

Detailed Description

The ERStat structure represents a class-specific Extremal Region (ER).

An ER is a 4-connected set of pixels with all its grey-level values smaller than the values in its outer boundary. A class-specific ER is selected (using a classifier) from all the ER's in the component tree of the image. :

Constructor & Destructor Documentation

§ ERStat()

cv::text::ERStat::ERStat ( int  level = 256,
int  pixel = 0,
int  x = 0,
int  y = 0 
)
explicit

Constructor.

§ ~ERStat()

cv::text::ERStat::~ERStat ( )
inline

Destructor.

Member Data Documentation

§ area

int cv::text::ERStat::area

incrementally computable features

§ central_moments

double cv::text::ERStat::central_moments[3]

order 2 central moments to construct the covariance matrix

§ child

ERStat* cv::text::ERStat::child

§ convex_hull_ratio

float cv::text::ERStat::convex_hull_ratio

§ crossings

Ptr<std::deque<int> > cv::text::ERStat::crossings

horizontal crossings

§ euler

int cv::text::ERStat::euler

Euler's number.

§ hole_area_ratio

float cv::text::ERStat::hole_area_ratio

2nd stage features

§ level

int cv::text::ERStat::level

§ local_maxima

bool cv::text::ERStat::local_maxima

whenever the regions is a local maxima of the probability

§ max_probability_ancestor

ERStat* cv::text::ERStat::max_probability_ancestor

§ med_crossings

float cv::text::ERStat::med_crossings

median of the crossings at three different height levels

§ min_probability_ancestor

ERStat* cv::text::ERStat::min_probability_ancestor

§ next

ERStat* cv::text::ERStat::next

§ num_inflexion_points

float cv::text::ERStat::num_inflexion_points

§ parent

ERStat* cv::text::ERStat::parent

pointers preserving the tree structure of the component tree

§ perimeter

int cv::text::ERStat::perimeter

§ pixel

int cv::text::ERStat::pixel

seed point and the threshold (max grey-level value)

§ pixels

std::vector<int>* cv::text::ERStat::pixels

§ prev

ERStat* cv::text::ERStat::prev

§ probability

double cv::text::ERStat::probability

probability that the ER belongs to the class we are looking for

§ raw_moments

double cv::text::ERStat::raw_moments[2]

order 1 raw moments to derive the centroid

§ rect

Rect cv::text::ERStat::rect

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