Expand description
§Extended Image Processing
§Structured forests for fast edge detection
This module contains implementations of modern structured edge detection algorithms, i.e. algorithms which somehow takes into account pixel affinities in natural images.
§EdgeBoxes
§Filters
§Superpixels
§Image segmentation
§Fast line detector
§EdgeDrawing
EDGE DRAWING LIBRARY FOR GEOMETRIC FEATURE EXTRACTION AND VALIDATION
Edge Drawing (ED) algorithm is an proactive approach on edge detection problem. In contrast to many other existing edge detection algorithms which follow a subtractive approach (i.e. after applying gradient filters onto an image eliminating pixels w.r.t. several rules, e.g. non-maximal suppression and hysteresis in Canny), ED algorithm works via an additive strategy, i.e. it picks edge pixels one by one, hence the name Edge Drawing. Then we process those random shaped edge segments to extract higher level edge features, i.e. lines, circles, ellipses, etc. The popular method of extraction edge pixels from the thresholded gradient magnitudes is non-maximal supression that tests every pixel whether it has the maximum gradient response along its gradient direction and eliminates if it does not. However, this method does not check status of the neighboring pixels, and therefore might result low quality (in terms of edge continuity, smoothness, thinness, localization) edge segments. Instead of non-maximal supression, ED points a set of edge pixels and join them by maximizing the total gradient response of edge segments. Therefore it can extract high quality edge segments without need for an additional hysteresis step.
§Fourier descriptors
§Binary morphology on run-length encoded image
These functions support morphological operations on binary images. In order to be fast and space efficient binary images are encoded with a run-length representation. This representation groups continuous horizontal sequences of “on” pixels together in a “run”. A run is charactarized by the column position of the first pixel in the run, the column position of the last pixel in the run and the row position. This representation is very compact for binary images which contain large continuous areas of “on” and “off” pixels. A checkerboard pattern would be a good example. The representation is not so suitable for binary images created from random noise images or other images where little correlation between neighboring pixels exists.
The morphological operations supported here are very similar to the operations supported in the imgproc module. In general they are fast. However on several occasions they are slower than the functions from imgproc. The structuring elements of cv::MORPH_RECT and cv::MORPH_CROSS have very good support from the imgproc module. Also small structuring elements are very fast in imgproc (presumably due to opencl support). Therefore the functions from this module are recommended for larger structuring elements (cv::MORPH_ELLIPSE or self defined structuring elements). A sample application (run_length_morphology_demo) is supplied which allows to compare the speed of some morphological operations for the functions using run-length encoding and the imgproc functions for a given image.
Run length encoded images are stored in standard opencv images. Images have a single column of cv::Point3i elements. The number of rows is the number of run + 1. The first row contains the size of the original (not encoded) image. For the runs the following mapping is used (x: column begin, y: column end (last column), z: row).
The size of the original image is required for compatibility with the imgproc functions when the boundary handling requires that pixel outside the image boundary are “on”.
Modules§
Structs§
- Adaptive
Manifold Filter - Interface for Adaptive Manifold Filter realizations.
- Box
- Contour
Fitting - Class for ContourFitting algorithms. ContourFitting match two contours inline formula and inline formula minimizing distance block formula where inline formula and inline formula are Fourier descriptors of inline formula and inline formula and s is a scaling factor and inline formula is angle rotation and inline formula is starting point factor adjustement
- DTFilter
- Interface for realizations of Domain Transform filter.
- Disparity
Filter - Main interface for all disparity map filters.
- DisparityWLS
Filter - Disparity map filter based on Weighted Least Squares filter (in form of Fast Global Smoother that is a lot faster than traditional Weighted Least Squares filter implementations) and optional use of left-right-consistency-based confidence to refine the results in half-occlusions and uniform areas.
- Edge
Aware Interpolator - Sparse match interpolation algorithm based on modified locally-weighted affine estimator from Revaud2015 and Fast Global Smoother as post-processing filter.
- Edge
Boxes - Class implementing EdgeBoxes algorithm from ZitnickECCV14edgeBoxes :
- Edge
Drawing - Class implementing the ED (EdgeDrawing) topal2012edge, EDLines akinlar2011edlines, EDPF akinlar2012edpf and EDCircles akinlar2013edcircles algorithms
- Edge
Drawing_ Params - Fast
Bilateral Solver Filter - Interface for implementations of Fast Bilateral Solver.
- Fast
Global Smoother Filter - Interface for implementations of Fast Global Smoother filter.
- Fast
Line Detector - @include samples/fld_lines.cpp
- Graph
Segmentation - Graph Based Segmentation Algorithm. The class implements the algorithm described in PFF2004 .
- Guided
Filter - Interface for realizations of (Fast) Guided Filter.
- RFFeature
Getter - ! Helper class for training part of [P. Dollar and C. L. Zitnick. Structured Forests for Fast Edge Detection, 2013].
- RICInterpolator
- Sparse match interpolation algorithm based on modified piecewise locally-weighted affine estimator called Robust Interpolation method of Correspondences or RIC from Hu2017 and Variational and Fast Global Smoother as post-processing filter. The RICInterpolator is a extension of the EdgeAwareInterpolator. Main concept of this extension is an piece-wise affine model based on over-segmentation via SLIC superpixel estimation. The method contains an efficient propagation mechanism to estimate among the pieces-wise models.
- Ridge
Detection Filter - Applies Ridge Detection Filter to an input image. Implements Ridge detection similar to the one in Mathematica using the eigen values from the Hessian Matrix of the input image using Sobel Derivatives. Additional refinement can be done using Skeletonization and Binarization. Adapted from segleafvein and M_RF
- Scan
Segment - Class implementing the F-DBSCAN (Accelerated superpixel image segmentation with a parallelized DBSCAN algorithm) superpixels algorithm by Loke SC, et al. loke2021accelerated for original paper.
- Selective
Search Segmentation - Selective search segmentation algorithm The class implements the algorithm described in uijlings2013selective.
- Selective
Search Segmentation Strategy - Strategie for the selective search segmentation algorithm The class implements a generic stragery for the algorithm described in uijlings2013selective.
- Selective
Search Segmentation Strategy Color - Color-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in uijlings2013selective.
- Selective
Search Segmentation Strategy Fill - Fill-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in uijlings2013selective.
- Selective
Search Segmentation Strategy Multiple - Regroup multiple strategies for the selective search segmentation algorithm
- Selective
Search Segmentation Strategy Size - Size-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in uijlings2013selective.
- Selective
Search Segmentation Strategy Texture - Texture-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in uijlings2013selective.
- Sparse
Match Interpolator - Main interface for all filters, that take sparse matches as an input and produce a dense per-pixel matching (optical flow) as an output.
- Structured
Edge Detection - Class implementing edge detection algorithm from Dollar2013 :
- SuperpixelLSC
- Class implementing the LSC (Linear Spectral Clustering) superpixels algorithm described in LiCVPR2015LSC.
- SuperpixelSEEDS
- Class implementing the SEEDS (Superpixels Extracted via Energy-Driven Sampling) superpixels algorithm described in VBRV14 .
- SuperpixelSLIC
- Class implementing the SLIC (Simple Linear Iterative Clustering) superpixels algorithm described in Achanta2012.
Enums§
- Angle
Range Option - Specifies the part of Hough space to calculate @details The enum specifies the part of Hough space to calculate. Each member specifies primarily direction of lines (horizontal or vertical) and the direction of angle changes. Direction of angle changes is from multiples of 90 to odd multiples of 45. The image considered to be written top-down and left-to-right. Angles are started from vertical line and go clockwise. Separate quarters and halves are written in orientation they should be in full Hough space.
- Edge
Aware Filters List - Edge
Drawing_ Gradient Operator - Hough
Deskew Option - Specifies to do or not to do skewing of Hough transform image @details The enum specifies to do or not to do skewing of Hough transform image so it would be no cycling in Hough transform image through borders of image.
- HoughOp
- Specifies binary operations. @details The enum specifies binary operations, that is such ones which involve two operands. Formally, a binary operation @f$ f @f$ on a set @f$ S @f$ is a binary relation that maps elements of the Cartesian product @f$ S \times S @f$ to @f$ S @f$: @f[ f: S \times S \to S @f]
- Local
Binarization Methods - Specifies the binarization method to use in cv::ximgproc::niBlackThreshold
- Rules
Option - Specifies the degree of rules validation. @details The enum specifies the degree of rules validation. This can be used, for example, to choose a proper way of input arguments validation.
- SLIC
Type - Thinning
Types - WMFWeight
Type - Specifies weight types of weighted median filter.
Constants§
- AM_
FILTER - ARO_
0_ 45 - ARO_
45_ 90 - ARO_
45_ 135 - ARO_
90_ 135 - ARO_
315_ 0 - ARO_
315_ 45 - ARO_
315_ 135 - ARO_
CTR_ HOR - ARO_
CTR_ VER - BINARIZATION_
NIBLACK - Classic Niblack binarization. See Niblack1985 .
- BINARIZATION_
NICK - NICK technique. See Khurshid2009 .
- BINARIZATION_
SAUVOLA - Sauvola’s technique. See Sauvola1997 .
- BINARIZATION_
WOLF - Wolf’s technique. See Wolf2004 .
- DTF_IC
- DTF_NC
- DTF_RF
- Edge
Drawing_ LSD - Edge
Drawing_ PREWITT - Edge
Drawing_ SCHARR - Edge
Drawing_ SOBEL - FHT_ADD
- FHT_AVE
- FHT_MAX
- FHT_MIN
- GUIDED_
FILTER - HDO_
DESKEW - HDO_RAW
- MSLIC
- RO_
IGNORE_ BORDERS - Skip validations of image borders.
- RO_
STRICT - Validate each rule in a proper way.
- SLIC
- SLICO
- THINNING_
GUOHALL - THINNING_
ZHANGSUEN - WMF_COS
- inline formula
- WMF_EXP
- inline formula
- WMF_IV1
- inline formula
- WMF_IV2
- inline formula
- WMF_JAC
- inline formula
- WMF_OFF
- unweighted
Traits§
- Adaptive
Manifold Filter Trait - Mutable methods for crate::ximgproc::AdaptiveManifoldFilter
- Adaptive
Manifold Filter Trait Const - Constant methods for crate::ximgproc::AdaptiveManifoldFilter
- Contour
Fitting Trait - Mutable methods for crate::ximgproc::ContourFitting
- Contour
Fitting Trait Const - Constant methods for crate::ximgproc::ContourFitting
- DTFilter
Trait - Mutable methods for crate::ximgproc::DTFilter
- DTFilter
Trait Const - Constant methods for crate::ximgproc::DTFilter
- Disparity
Filter Trait - Mutable methods for crate::ximgproc::DisparityFilter
- Disparity
Filter Trait Const - Constant methods for crate::ximgproc::DisparityFilter
- DisparityWLS
Filter Trait - Mutable methods for crate::ximgproc::DisparityWLSFilter
- DisparityWLS
Filter Trait Const - Constant methods for crate::ximgproc::DisparityWLSFilter
- Edge
Aware Interpolator Trait - Mutable methods for crate::ximgproc::EdgeAwareInterpolator
- Edge
Aware Interpolator Trait Const - Constant methods for crate::ximgproc::EdgeAwareInterpolator
- Edge
Boxes Trait - Mutable methods for crate::ximgproc::EdgeBoxes
- Edge
Boxes Trait Const - Constant methods for crate::ximgproc::EdgeBoxes
- Edge
Drawing Trait - Mutable methods for crate::ximgproc::EdgeDrawing
- Edge
Drawing Trait Const - Constant methods for crate::ximgproc::EdgeDrawing
- Fast
Bilateral Solver Filter Trait - Mutable methods for crate::ximgproc::FastBilateralSolverFilter
- Fast
Bilateral Solver Filter Trait Const - Constant methods for crate::ximgproc::FastBilateralSolverFilter
- Fast
Global Smoother Filter Trait - Mutable methods for crate::ximgproc::FastGlobalSmootherFilter
- Fast
Global Smoother Filter Trait Const - Constant methods for crate::ximgproc::FastGlobalSmootherFilter
- Fast
Line Detector Trait - Mutable methods for crate::ximgproc::FastLineDetector
- Fast
Line Detector Trait Const - Constant methods for crate::ximgproc::FastLineDetector
- Graph
Segmentation Trait - Mutable methods for crate::ximgproc::GraphSegmentation
- Graph
Segmentation Trait Const - Constant methods for crate::ximgproc::GraphSegmentation
- Guided
Filter Trait - Mutable methods for crate::ximgproc::GuidedFilter
- Guided
Filter Trait Const - Constant methods for crate::ximgproc::GuidedFilter
- RFFeature
Getter Trait - Mutable methods for crate::ximgproc::RFFeatureGetter
- RFFeature
Getter Trait Const - Constant methods for crate::ximgproc::RFFeatureGetter
- RICInterpolator
Trait - Mutable methods for crate::ximgproc::RICInterpolator
- RICInterpolator
Trait Const - Constant methods for crate::ximgproc::RICInterpolator
- Ridge
Detection Filter Trait - Mutable methods for crate::ximgproc::RidgeDetectionFilter
- Ridge
Detection Filter Trait Const - Constant methods for crate::ximgproc::RidgeDetectionFilter
- Scan
Segment Trait - Mutable methods for crate::ximgproc::ScanSegment
- Scan
Segment Trait Const - Constant methods for crate::ximgproc::ScanSegment
- Selective
Search Segmentation Strategy Color Trait - Mutable methods for crate::ximgproc::SelectiveSearchSegmentationStrategyColor
- Selective
Search Segmentation Strategy Color Trait Const - Constant methods for crate::ximgproc::SelectiveSearchSegmentationStrategyColor
- Selective
Search Segmentation Strategy Fill Trait - Mutable methods for crate::ximgproc::SelectiveSearchSegmentationStrategyFill
- Selective
Search Segmentation Strategy Fill Trait Const - Constant methods for crate::ximgproc::SelectiveSearchSegmentationStrategyFill
- Selective
Search Segmentation Strategy Multiple Trait - Mutable methods for crate::ximgproc::SelectiveSearchSegmentationStrategyMultiple
- Selective
Search Segmentation Strategy Multiple Trait Const - Constant methods for crate::ximgproc::SelectiveSearchSegmentationStrategyMultiple
- Selective
Search Segmentation Strategy Size Trait - Mutable methods for crate::ximgproc::SelectiveSearchSegmentationStrategySize
- Selective
Search Segmentation Strategy Size Trait Const - Constant methods for crate::ximgproc::SelectiveSearchSegmentationStrategySize
- Selective
Search Segmentation Strategy Texture Trait - Mutable methods for crate::ximgproc::SelectiveSearchSegmentationStrategyTexture
- Selective
Search Segmentation Strategy Texture Trait Const - Constant methods for crate::ximgproc::SelectiveSearchSegmentationStrategyTexture
- Selective
Search Segmentation Strategy Trait - Mutable methods for crate::ximgproc::SelectiveSearchSegmentationStrategy
- Selective
Search Segmentation Strategy Trait Const - Constant methods for crate::ximgproc::SelectiveSearchSegmentationStrategy
- Selective
Search Segmentation Trait - Mutable methods for crate::ximgproc::SelectiveSearchSegmentation
- Selective
Search Segmentation Trait Const - Constant methods for crate::ximgproc::SelectiveSearchSegmentation
- Sparse
Match Interpolator Trait - Mutable methods for crate::ximgproc::SparseMatchInterpolator
- Sparse
Match Interpolator Trait Const - Constant methods for crate::ximgproc::SparseMatchInterpolator
- Structured
Edge Detection Trait - Mutable methods for crate::ximgproc::StructuredEdgeDetection
- Structured
Edge Detection Trait Const - Constant methods for crate::ximgproc::StructuredEdgeDetection
- SuperpixelLSC
Trait - Mutable methods for crate::ximgproc::SuperpixelLSC
- SuperpixelLSC
Trait Const - Constant methods for crate::ximgproc::SuperpixelLSC
- SuperpixelSEEDS
Trait - Mutable methods for crate::ximgproc::SuperpixelSEEDS
- SuperpixelSEEDS
Trait Const - Constant methods for crate::ximgproc::SuperpixelSEEDS
- SuperpixelSLIC
Trait - Mutable methods for crate::ximgproc::SuperpixelSLIC
- SuperpixelSLIC
Trait Const - Constant methods for crate::ximgproc::SuperpixelSLIC
Functions§
- am_
filter - Simple one-line Adaptive Manifold Filter call.
- am_
filter_ def - Simple one-line Adaptive Manifold Filter call.
- anisotropic_
diffusion - Performs anisotropic diffusion on an image.
- bilateral_
texture_ filter - Applies the bilateral texture filter to an image. It performs structure-preserving texture filter. For more details about this filter see Cho2014.
- bilateral_
texture_ filter_ def - Applies the bilateral texture filter to an image. It performs structure-preserving texture filter. For more details about this filter see Cho2014.
- bright_
edges - C++ default parameters
- bright_
edges_ def - Note
- color_
match_ template - Compares a color template against overlapped color image regions.
- compute_
bad_ pixel_ percent - Function for computing the percent of “bad” pixels in the disparity map (pixels where error is higher than a specified threshold)
- compute_
bad_ pixel_ percent_ def - Function for computing the percent of “bad” pixels in the disparity map (pixels where error is higher than a specified threshold)
- compute_
mse - Function for computing mean square error for disparity maps
- contour_
sampling - Contour sampling .
- covariance_
estimation - Computes the estimated covariance matrix of an image using the sliding window forumlation.
- create_
am_ filter - Factory method, create instance of AdaptiveManifoldFilter and produce some initialization routines.
- create_
am_ filter_ def - Factory method, create instance of AdaptiveManifoldFilter and produce some initialization routines.
- create_
contour_ fitting - create ContourFitting algorithm object
- create_
contour_ fitting_ def - create ContourFitting algorithm object
- create_
disparity_ wls_ filter - Convenience factory method that creates an instance of DisparityWLSFilter and sets up all the relevant filter parameters automatically based on the matcher instance. Currently supports only StereoBM and StereoSGBM.
- create_
disparity_ wls_ filter_ generic - More generic factory method, create instance of DisparityWLSFilter and execute basic initialization routines. When using this method you will need to set-up the ROI, matchers and other parameters by yourself.
- create_
dt_ filter - Factory method, create instance of DTFilter and produce initialization routines.
- create_
dt_ filter_ def - Factory method, create instance of DTFilter and produce initialization routines.
- create_
edge_ aware_ interpolator - Factory method that creates an instance of the EdgeAwareInterpolator.
- create_
edge_ boxes - Creates a Edgeboxes
- create_
edge_ boxes_ def - Creates a Edgeboxes
- create_
edge_ drawing - Creates a smart pointer to a EdgeDrawing object and initializes it
- create_
fast_ bilateral_ solver_ filter - Factory method, create instance of FastBilateralSolverFilter and execute the initialization routines.
- create_
fast_ bilateral_ solver_ filter_ def - Factory method, create instance of FastBilateralSolverFilter and execute the initialization routines.
- create_
fast_ global_ smoother_ filter - Factory method, create instance of FastGlobalSmootherFilter and execute the initialization routines.
- create_
fast_ global_ smoother_ filter_ def - Factory method, create instance of FastGlobalSmootherFilter and execute the initialization routines.
- create_
fast_ line_ detector - Creates a smart pointer to a FastLineDetector object and initializes it
- create_
fast_ line_ detector_ def - Creates a smart pointer to a FastLineDetector object and initializes it
- create_
graph_ segmentation - Creates a graph based segmentor
- create_
graph_ segmentation_ def - Creates a graph based segmentor
- create_
guided_ filter - Factory method, create instance of GuidedFilter and produce initialization routines.
- create_
guided_ filter_ def - Factory method, create instance of GuidedFilter and produce initialization routines.
- create_
quaternion_ image - creates a quaternion image.
- create_
rf_ feature_ getter - create_
ric_ interpolator - Factory method that creates an instance of the RICInterpolator.
- create_
right_ matcher - Convenience method to set up the matcher for computing the right-view disparity map that is required in case of filtering with confidence.
- create_
rle_ image - Creates a run-length encoded image from a vector of runs (column begin, column end, row)
- create_
rle_ image_ def - Creates a run-length encoded image from a vector of runs (column begin, column end, row)
- create_
scan_ segment - Initializes a ScanSegment object.
- create_
scan_ segment_ def - Initializes a ScanSegment object.
- create_
selective_ search_ segmentation - Create a new SelectiveSearchSegmentation class.
- create_
selective_ search_ segmentation_ strategy_ color - Create a new color-based strategy
- create_
selective_ search_ segmentation_ strategy_ fill - Create a new fill-based strategy
- create_
selective_ search_ segmentation_ strategy_ multiple - Create a new multiple strategy
- create_
selective_ search_ segmentation_ strategy_ multiple_ 1 - Create a new multiple strategy and set one subtrategy
- create_
selective_ search_ segmentation_ strategy_ multiple_ 2 - Create a new multiple strategy and set two subtrategies, with equal weights
- create_
selective_ search_ segmentation_ strategy_ multiple_ 3 - Create a new multiple strategy and set three subtrategies, with equal weights
- create_
selective_ search_ segmentation_ strategy_ multiple_ 4 - Create a new multiple strategy and set four subtrategies, with equal weights
- create_
selective_ search_ segmentation_ strategy_ size - Create a new size-based strategy
- create_
selective_ search_ segmentation_ strategy_ texture - Create a new size-based strategy
- create_
structured_ edge_ detection - !
- create_
structured_ edge_ detection_ def - !
- create_
superpixel_ lsc - Class implementing the LSC (Linear Spectral Clustering) superpixels
- create_
superpixel_ lsc_ def - Class implementing the LSC (Linear Spectral Clustering) superpixels
- create_
superpixel_ seeds - Initializes a SuperpixelSEEDS object.
- create_
superpixel_ seeds_ def - Initializes a SuperpixelSEEDS object.
- create_
superpixel_ slic - Initialize a SuperpixelSLIC object
- create_
superpixel_ slic_ def - Initialize a SuperpixelSLIC object
- dilate
- Dilates an run-length encoded binary image by using a specific structuring element.
- dilate_
def - Dilates an run-length encoded binary image by using a specific structuring element.
- dt_
filter - Simple one-line Domain Transform filter call. If you have multiple images to filter with the same guided image then use DTFilter interface to avoid extra computations on initialization stage.
- dt_
filter_ def - Simple one-line Domain Transform filter call. If you have multiple images to filter with the same guided image then use DTFilter interface to avoid extra computations on initialization stage.
- edge_
preserving_ filter - Smoothes an image using the Edge-Preserving filter.
- erode
- Erodes an run-length encoded binary image by using a specific structuring element.
- erode_
def - Erodes an run-length encoded binary image by using a specific structuring element.
- fast_
bilateral_ solver_ filter - Simple one-line Fast Bilateral Solver filter call. If you have multiple images to filter with the same guide then use FastBilateralSolverFilter interface to avoid extra computations.
- fast_
bilateral_ solver_ filter_ def - Simple one-line Fast Bilateral Solver filter call. If you have multiple images to filter with the same guide then use FastBilateralSolverFilter interface to avoid extra computations.
- fast_
global_ smoother_ filter - Simple one-line Fast Global Smoother filter call. If you have multiple images to filter with the same guide then use FastGlobalSmootherFilter interface to avoid extra computations.
- fast_
global_ smoother_ filter_ def - Simple one-line Fast Global Smoother filter call. If you have multiple images to filter with the same guide then use FastGlobalSmootherFilter interface to avoid extra computations.
- fast_
hough_ transform - Calculates 2D Fast Hough transform of an image.
- fast_
hough_ transform_ def - Calculates 2D Fast Hough transform of an image.
- find_
ellipses - Finds ellipses fastly in an image using projective invariant pruning. *
- find_
ellipses_ def - Finds ellipses fastly in an image using projective invariant pruning. *
- fourier_
descriptor - Fourier descriptors for planed closed curves
- fourier_
descriptor_ def - Fourier descriptors for planed closed curves
- get_
disparity_ vis - Function for creating a disparity map visualization (clamped CV_8U image)
- get_
disparity_ vis_ def - Function for creating a disparity map visualization (clamped CV_8U image)
- get_
structuring_ element - Returns a run length encoded structuring element of the specified size and shape.
- gradient_
deriche_ x - Applies X Deriche filter to an image.
- gradient_
deriche_ y - Applies Y Deriche filter to an image.
- gradient_
paillou_ x - gradient_
paillou_ y - Applies Paillou filter to an image.
- guided_
filter - Simple one-line (Fast) Guided Filter call.
- guided_
filter_ def - Simple one-line (Fast) Guided Filter call.
- hough_
point2_ line - Calculates coordinates of line segment corresponded by point in Hough space.
- hough_
point2_ line_ def - Calculates coordinates of line segment corresponded by point in Hough space.
- is_
rl_ morphology_ possible - Check whether a custom made structuring element can be used with run length morphological operations. (It must consist of a continuous array of single runs per row)
- joint_
bilateral_ filter - Applies the joint bilateral filter to an image.
- joint_
bilateral_ filter_ def - Applies the joint bilateral filter to an image.
- l0_
smooth - Global image smoothing via L0 gradient minimization.
- l0_
smooth_ def - Global image smoothing via L0 gradient minimization.
- morphology_
ex - Applies a morphological operation to a run-length encoded binary image.
- morphology_
ex_ def - Applies a morphological operation to a run-length encoded binary image.
- ni_
black_ threshold - Performs thresholding on input images using Niblack’s technique or some of the popular variations it inspired.
- ni_
black_ threshold_ def - Performs thresholding on input images using Niblack’s technique or some of the popular variations it inspired.
- paint
- Paint run length encoded binary image into an image.
- pei_
lin_ normalization - Calculates an affine transformation that normalize given image using Pei&Lin Normalization.
- pei_
lin_ normalization_ 1 - Calculates an affine transformation that normalize given image using Pei&Lin Normalization.
- qconj
- calculates conjugate of a quaternion image.
- qdft
- Performs a forward or inverse Discrete quaternion Fourier transform of a 2D quaternion array.
- qmultiply
- Calculates the per-element quaternion product of two arrays
- qunitary
- divides each element by its modulus.
- radon_
transform - Calculate Radon Transform of an image.
- radon_
transform_ def - Calculate Radon Transform of an image.
- read_gt
- Function for reading ground truth disparity maps. Supports basic Middlebury and MPI-Sintel formats. Note that the resulting disparity map is scaled by 16.
- rolling_
guidance_ filter - Applies the rolling guidance filter to an image.
- rolling_
guidance_ filter_ def - Applies the rolling guidance filter to an image.
- thinning
- Applies a binary blob thinning operation, to achieve a skeletization of the input image.
- thinning_
def - Applies a binary blob thinning operation, to achieve a skeletization of the input image.
- threshold
- Applies a fixed-level threshold to each array element.
- transform_
fd - transform a contour
- transform_
fd_ def - transform a contour
- weighted_
median_ filter - Applies weighted median filter to an image.
- weighted_
median_ filter_ def - Applies weighted median filter to an image.