Module opencv::cudaimgproc

Image Processing

Color space processing

Histogram Calculation

Structural Analysis and Shape Descriptors

Hough Transform

Feature Detection

Modules

• prelude

Structs

• CUDA_CLAHE
  Base class for Contrast Limited Adaptive Histogram Equalization. :
• CUDA_CannyEdgeDetector
  Base class for Canny Edge Detector. :
• CUDA_CornernessCriteria
  Base class for Cornerness Criteria computation. :
• CUDA_CornersDetector
  Base class for Corners Detector. :
• CUDA_HoughCirclesDetector
  Base class for circles detector algorithm. :
• CUDA_HoughLinesDetector
  Base class for lines detector algorithm. :
• CUDA_HoughSegmentDetector
  Base class for line segments detector algorithm. :
• CUDA_TemplateMatching
  Base class for Template Matching. :

Enums

• CUDA_AlphaCompTypes
• CUDA_ConnectedComponentsAlgorithmsTypes
  Connected Components Algorithm
• CUDA_DemosaicTypes
• CUDA_MomentsOrder
  Order of image moments.

Constants

• CUDA_ALPHA_ATOP
• CUDA_ALPHA_ATOP_PREMUL
• CUDA_ALPHA_IN
• CUDA_ALPHA_IN_PREMUL
• CUDA_ALPHA_OUT
• CUDA_ALPHA_OUT_PREMUL
• CUDA_ALPHA_OVER
• CUDA_ALPHA_OVER_PREMUL
• CUDA_ALPHA_PLUS
• CUDA_ALPHA_PLUS_PREMUL
• CUDA_ALPHA_PREMUL
• CUDA_ALPHA_XOR
• CUDA_ALPHA_XOR_PREMUL
• CUDA_CCL_BKE
  BKE Allegretti2019 algorithm for 8-way connectivity.
• CUDA_CCL_DEFAULT
  BKE Allegretti2019 algorithm for 8-way connectivity.
• CUDA_COLOR_BayerBG2BGR_MHT
  Bayer Demosaicing (Malvar, He, and Cutler)
• CUDA_COLOR_BayerBG2GRAY_MHT
  Bayer Demosaicing (Malvar, He, and Cutler)
• CUDA_COLOR_BayerBG2RGB_MHT
  Bayer Demosaicing (Malvar, He, and Cutler)
• CUDA_COLOR_BayerGB2BGR_MHT
  Bayer Demosaicing (Malvar, He, and Cutler)
• CUDA_COLOR_BayerGB2GRAY_MHT
  Bayer Demosaicing (Malvar, He, and Cutler)
• CUDA_COLOR_BayerGB2RGB_MHT
  Bayer Demosaicing (Malvar, He, and Cutler)
• CUDA_COLOR_BayerGR2BGR_MHT
  Bayer Demosaicing (Malvar, He, and Cutler)
• CUDA_COLOR_BayerGR2GRAY_MHT
  Bayer Demosaicing (Malvar, He, and Cutler)
• CUDA_COLOR_BayerGR2RGB_MHT
  Bayer Demosaicing (Malvar, He, and Cutler)
• CUDA_COLOR_BayerRG2BGR_MHT
  Bayer Demosaicing (Malvar, He, and Cutler)
• CUDA_COLOR_BayerRG2GRAY_MHT
  Bayer Demosaicing (Malvar, He, and Cutler)
• CUDA_COLOR_BayerRG2RGB_MHT
  Bayer Demosaicing (Malvar, He, and Cutler)
• CUDA_FIRST_ORDER_MOMENTS
• CUDA_SECOND_ORDER_MOMENTS
• CUDA_THIRD_ORDER_MOMENTS

Traits

• CUDA_CLAHETrait
  Mutable methods for crate::cudaimgproc::CUDA_CLAHE
• CUDA_CLAHETraitConst
  Constant methods for crate::cudaimgproc::CUDA_CLAHE
• CUDA_CannyEdgeDetectorTrait
  Mutable methods for crate::cudaimgproc::CUDA_CannyEdgeDetector
• CUDA_CannyEdgeDetectorTraitConst
  Constant methods for crate::cudaimgproc::CUDA_CannyEdgeDetector
• CUDA_CornernessCriteriaTrait
  Mutable methods for crate::cudaimgproc::CUDA_CornernessCriteria
• CUDA_CornernessCriteriaTraitConst
  Constant methods for crate::cudaimgproc::CUDA_CornernessCriteria
• CUDA_CornersDetectorTrait
  Mutable methods for crate::cudaimgproc::CUDA_CornersDetector
• CUDA_CornersDetectorTraitConst
  Constant methods for crate::cudaimgproc::CUDA_CornersDetector
• CUDA_HoughCirclesDetectorTrait
  Mutable methods for crate::cudaimgproc::CUDA_HoughCirclesDetector
• CUDA_HoughCirclesDetectorTraitConst
  Constant methods for crate::cudaimgproc::CUDA_HoughCirclesDetector
• CUDA_HoughLinesDetectorTrait
  Mutable methods for crate::cudaimgproc::CUDA_HoughLinesDetector
• CUDA_HoughLinesDetectorTraitConst
  Constant methods for crate::cudaimgproc::CUDA_HoughLinesDetector
• CUDA_HoughSegmentDetectorTrait
  Mutable methods for crate::cudaimgproc::CUDA_HoughSegmentDetector
• CUDA_HoughSegmentDetectorTraitConst
  Constant methods for crate::cudaimgproc::CUDA_HoughSegmentDetector
• CUDA_TemplateMatchingTrait
  Mutable methods for crate::cudaimgproc::CUDA_TemplateMatching
• CUDA_TemplateMatchingTraitConst
  Constant methods for crate::cudaimgproc::CUDA_TemplateMatching

Functions

• alpha_comp
  Composites two images using alpha opacity values contained in each image.
• alpha_comp_def
  Composites two images using alpha opacity values contained in each image.
• bilateral_filter
  Performs bilateral filtering of passed image
• bilateral_filter_def
  Performs bilateral filtering of passed image
• blend_linear
  Performs linear blending of two images.
• blend_linear_def
  Performs linear blending of two images.
• calc_hist
  Calculates histogram for one channel 8-bit image.
• calc_hist_1
  Calculates histogram for one channel 8-bit image confined in given mask.
• calc_hist_1_def
  Calculates histogram for one channel 8-bit image confined in given mask.
• calc_hist_def
  Calculates histogram for one channel 8-bit image.
• connected_components
  Computes the Connected Components Labeled image of a binary image.
• connected_components_def
  @overload
• connected_components_with_algorithm
  Computes the Connected Components Labeled image of a binary image.
• create_canny_edge_detector
  Creates implementation for cuda::CannyEdgeDetector .
• create_canny_edge_detector_def
  Creates implementation for cuda::CannyEdgeDetector .
• create_clahe
  Creates implementation for cuda::CLAHE .
• create_clahe_def
  Creates implementation for cuda::CLAHE .
• create_generalized_hough_ballard
  Creates implementation for generalized hough transform from Ballard1981 .
• create_generalized_hough_guil
  Creates implementation for generalized hough transform from Guil1999 .
• create_good_features_to_track_detector
  Creates implementation for cuda::CornersDetector .
• create_good_features_to_track_detector_def
  Creates implementation for cuda::CornersDetector .
• create_harris_corner
  Creates implementation for Harris cornerness criteria.
• create_harris_corner_def
  Creates implementation for Harris cornerness criteria.
• create_hough_circles_detector
  Creates implementation for cuda::HoughCirclesDetector .
• create_hough_circles_detector_def
  Creates implementation for cuda::HoughCirclesDetector .
• create_hough_lines_detector
  Creates implementation for cuda::HoughLinesDetector .
• create_hough_lines_detector_def
  Creates implementation for cuda::HoughLinesDetector .
• create_hough_segment_detector
  Creates implementation for cuda::HoughSegmentDetector .
• create_hough_segment_detector_def
  Creates implementation for cuda::HoughSegmentDetector .
• create_min_eigen_val_corner
  Creates implementation for the minimum eigen value of a 2x2 derivative covariation matrix (the cornerness criteria).
• create_min_eigen_val_corner_def
  Creates implementation for the minimum eigen value of a 2x2 derivative covariation matrix (the cornerness criteria).
• create_template_matching
  Creates implementation for cuda::TemplateMatching .
• create_template_matching_def
  Creates implementation for cuda::TemplateMatching .
• cvt_color
  Converts an image from one color space to another.
• cvt_color_def
  Converts an image from one color space to another.
• demosaicing
  Converts an image from Bayer pattern to RGB or grayscale.
• demosaicing_def
  Converts an image from Bayer pattern to RGB or grayscale.
• equalize_hist
  Equalizes the histogram of a grayscale image.
• equalize_hist_def
  Equalizes the histogram of a grayscale image.
• even_levels
  Computes levels with even distribution.
• even_levels_def
  Computes levels with even distribution.
• gamma_correction
  Routines for correcting image color gamma.
• gamma_correction_def
  Routines for correcting image color gamma.
• hist_even
  Calculates a histogram with evenly distributed bins.
• hist_even_def
  Calculates a histogram with evenly distributed bins.
• hist_range
  Calculates a histogram with bins determined by the levels array.
• hist_range_def
  Calculates a histogram with bins determined by the levels array.
• mean_shift_filtering
  Performs mean-shift filtering for each point of the source image.
• mean_shift_filtering_def
  Performs mean-shift filtering for each point of the source image.
• mean_shift_proc
  Performs a mean-shift procedure and stores information about processed points (their colors and positions) in two images.
• mean_shift_proc_def
  Performs a mean-shift procedure and stores information about processed points (their colors and positions) in two images.
• mean_shift_segmentation
  Performs a mean-shift segmentation of the source image and eliminates small segments.
• mean_shift_segmentation_def
  Performs a mean-shift segmentation of the source image and eliminates small segments.
• moments
  Calculates all of the moments up to the 3rd order of a rasterized shape.
• moments_def
  Calculates all of the moments up to the 3rd order of a rasterized shape.
• num_moments
  Returns the number of image moments less than or equal to the largest image moments \a order.
• spatial_moments
  Calculates all of the spatial moments up to the 3rd order of a rasterized shape.
• spatial_moments_def
  Calculates all of the spatial moments up to the 3rd order of a rasterized shape.
• swap_channels
  Exchanges the color channels of an image in-place.
• swap_channels_def
  Exchanges the color channels of an image in-place.