Image Processing

Overview

Color space processing
Feature Detection
Histogram Calculation
Hough Transform

// classes

class cv::cuda::CannyEdgeDetector;
class cv::cuda::TemplateMatching;

// global functions

void
cv::cuda::bilateralFilter(
    InputArray src,
    OutputArray dst,
    int kernel_size,
    float sigma_color,
    float sigma_spatial,
    int borderMode = BORDER_DEFAULT,
    Stream& stream = Stream::Null()
    );

void
cv::cuda::blendLinear(
    InputArray img1,
    InputArray img2,
    InputArray weights1,
    InputArray weights2,
    OutputArray result,
    Stream& stream = Stream::Null()
    );

Ptr<CannyEdgeDetector>
cv::cuda::createCannyEdgeDetector(
    double low_thresh,
    double high_thresh,
    int apperture_size = 3,
    bool L2gradient = false
    );

Ptr<TemplateMatching>
cv::cuda::createTemplateMatching(
    int srcType,
    int method,
    Size user_block_size = Size()
    );

void
cv::cuda::meanShiftFiltering(
    InputArray src,
    OutputArray dst,
    int sp,
    int sr,
    TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 1),
    Stream& stream = Stream::Null()
    );

void
cv::cuda::meanShiftProc(
    InputArray src,
    OutputArray dstr,
    OutputArray dstsp,
    int sp,
    int sr,
    TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 1),
    Stream& stream = Stream::Null()
    );

void
cv::cuda::meanShiftSegmentation(
    InputArray src,
    OutputArray dst,
    int sp,
    int sr,
    int minsize,
    TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 1),
    Stream& stream = Stream::Null()
    );

Detailed Documentation

Global Functions

void
cv::cuda::bilateralFilter(
    InputArray src,
    OutputArray dst,
    int kernel_size,
    float sigma_color,
    float sigma_spatial,
    int borderMode = BORDER_DEFAULT,
    Stream& stream = Stream::Null()
    )

Performs bilateral filtering of passed image.

Parameters:

src	Source image. Supports only (channles != 2 && depth() != CV_8S && depth() != CV_32S && depth() != CV_64F).
dst	Destination imagwe.
kernel_size	Kernel window size.
sigma_color	Filter sigma in the color space.
sigma_spatial	Filter sigma in the coordinate space.
borderMode	Border type. See borderInterpolate for details. BORDER_REFLECT101 , BORDER_REPLICATE , BORDER_CONSTANT , BORDER_REFLECT and BORDER_WRAP are supported for now.
stream	Stream for the asynchronous version.

See also:

bilateralFilter

void
cv::cuda::blendLinear(
    InputArray img1,
    InputArray img2,
    InputArray weights1,
    InputArray weights2,
    OutputArray result,
    Stream& stream = Stream::Null()
    )

Performs linear blending of two images.

Parameters:

img1	First image. Supports only CV_8U and CV_32F depth.
img2	Second image. Must have the same size and the same type as img1 .
weights1	Weights for first image. Must have tha same size as img1 . Supports only CV_32F type.
weights2	Weights for second image. Must have tha same size as img2 . Supports only CV_32F type.
result	Destination image.
stream	Stream for the asynchronous version.

Ptr<CannyEdgeDetector>
cv::cuda::createCannyEdgeDetector(
    double low_thresh,
    double high_thresh,
    int apperture_size = 3,
    bool L2gradient = false
    )

Creates implementation for cuda::CannyEdgeDetector.

Parameters:

low_thresh	First threshold for the hysteresis procedure.
high_thresh	Second threshold for the hysteresis procedure.
apperture_size	Aperture size for the Sobel operator.
L2gradient	Flag indicating whether a more accurate \(L_2\) norm \(=\sqrt{(dI/dx)^2 + (dI/dy)^2}\) should be used to compute the image gradient magnitude ( L2gradient=true ), or a faster default \(L_1\) norm \(=\|dI/dx\|+\|dI/dy\|\) is enough ( L2gradient=false ).

Ptr<TemplateMatching>
cv::cuda::createTemplateMatching(
    int srcType,
    int method,
    Size user_block_size = Size()
    )

Creates implementation for cuda::TemplateMatching.

The following methods are supported for the CV_8U depth images for now:

CV_TM_SQDIFF
CV_TM_SQDIFF_NORMED
CV_TM_CCORR
CV_TM_CCORR_NORMED
CV_TM_CCOEFF
CV_TM_CCOEFF_NORMED

The following methods are supported for the CV_32F images for now:

CV_TM_SQDIFF
CV_TM_CCORR

Parameters:

srcType	Input source type. CV_32F and CV_8U depth images (1..4 channels) are supported for now.
method	Specifies the way to compare the template with the image.
user_block_size	You can use field user_block_size to set specific block size. If you leave its default value Size(0,0) then automatic estimation of block size will be used (which is optimized for speed). By varying user_block_size you can reduce memory requirements at the cost of speed.

See also:

matchTemplate

void
cv::cuda::meanShiftFiltering(
    InputArray src,
    OutputArray dst,
    int sp,
    int sr,
    TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 1),
    Stream& stream = Stream::Null()
    )

Performs mean-shift filtering for each point of the source image.

It maps each point of the source image into another point. As a result, you have a new color and new position of each point.

Parameters:

src	Source image. Only CV_8UC4 images are supported for now.
dst	Destination image containing the color of mapped points. It has the same size and type as src .
sp	Spatial window radius.
sr	Color window radius.
criteria	Termination criteria. See TermCriteria.
stream	Stream for the asynchronous version.

void
cv::cuda::meanShiftProc(
    InputArray src,
    OutputArray dstr,
    OutputArray dstsp,
    int sp,
    int sr,
    TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 1),
    Stream& stream = Stream::Null()
    )

Performs a mean-shift procedure and stores information about processed points (their colors and positions) in two images.

Parameters:

src	Source image. Only CV_8UC4 images are supported for now.
dstr	Destination image containing the color of mapped points. The size and type is the same as src .
dstsp	Destination image containing the position of mapped points. The size is the same as src size. The type is CV_16SC2 .
sp	Spatial window radius.
sr	Color window radius.
criteria	Termination criteria. See TermCriteria.
stream	Stream for the asynchronous version.