OpenCV  3.2.0
Open Source Computer Vision
Modules | Classes | Enumerations | Functions
Image processing

Modules

 Image Filtering
 
 Imgproc_transform
 
 Imgproc_misc
 
 Imgproc_shape
 
 Imgproc_subdiv2d
 
 Imgproc_feature
 
 Imgproc_motion
 
 Imgproc_hist
 
 Imgproc_object
 
 Imgproc_colormap
 
 Imgproc_draw
 

Classes

class  cv::CLAHE
 
class  cv::GeneralizedHough
 finds arbitrary template in the grayscale image using Generalized Hough Transform More...
 
class  cv::GeneralizedHoughBallard
 
class  cv::GeneralizedHoughGuil
 

Enumerations

enum  cv::HoughModes {
  cv::HOUGH_STANDARD = 0,
  cv::HOUGH_PROBABILISTIC = 1,
  cv::HOUGH_MULTI_SCALE = 2,
  cv::HOUGH_GRADIENT = 3
}
 Variants of a Hough transform. More...
 

Functions

void cv::blendLinear (InputArray src1, InputArray src2, InputArray weights1, InputArray weights2, OutputArray dst)
 Performs linear blending of two images. More...
 
Ptr< CLAHEcv::createCLAHE (double clipLimit=40.0, Size tileGridSize=Size(8, 8))
 
Ptr< GeneralizedHoughBallardcv::createGeneralizedHoughBallard ()
 
Ptr< GeneralizedHoughGuilcv::createGeneralizedHoughGuil ()
 
void cv::demosaicing (InputArray _src, OutputArray _dst, int code, int dcn=0)
 

Detailed Description

Enumeration Type Documentation

◆ HoughModes

Variants of a Hough transform.

Enumerator
HOUGH_STANDARD 

classical or standard Hough transform. Every line is represented by two floating-point numbers \((\rho, \theta)\) , where \(\rho\) is a distance between (0,0) point and the line, and \(\theta\) is the angle between x-axis and the normal to the line. Thus, the matrix must be (the created sequence will be) of CV_32FC2 type

HOUGH_PROBABILISTIC 

probabilistic Hough transform (more efficient in case if the picture contains a few long linear segments). It returns line segments rather than the whole line. Each segment is represented by starting and ending points, and the matrix must be (the created sequence will be) of the CV_32SC4 type.

HOUGH_MULTI_SCALE 

multi-scale variant of the classical Hough transform. The lines are encoded the same way as HOUGH_STANDARD.

HOUGH_GRADIENT 

basically 21HT, described in [Yuen90]

Function Documentation

◆ blendLinear()

void cv::blendLinear ( InputArray  src1,
InputArray  src2,
InputArray  weights1,
InputArray  weights2,
OutputArray  dst 
)

Performs linear blending of two images.

◆ createCLAHE()

Ptr<CLAHE> cv::createCLAHE ( double  clipLimit = 40.0,
Size  tileGridSize = Size(8, 8) 
)

◆ createGeneralizedHoughBallard()

Ptr<GeneralizedHoughBallard> cv::createGeneralizedHoughBallard ( )

Ballard, D.H. (1981). Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13 (2): 111-122. Detects position only without traslation and rotation

◆ createGeneralizedHoughGuil()

Ptr<GeneralizedHoughGuil> cv::createGeneralizedHoughGuil ( )

Guil, N., González-Linares, J.M. and Zapata, E.L. (1999). Bidimensional shape detection using an invariant approach. Pattern Recognition 32 (6): 1025-1038. Detects position, traslation and rotation

◆ demosaicing()

void cv::demosaicing ( InputArray  _src,
OutputArray  _dst,
int  code,
int  dcn = 0 
)