C API
[Image processing]

Freeman chain reader state.

Connected component structure.

Convexity defect.

Font structure.

Hu invariants.

Spatial and central moments.

Filters used in pyramid decomposition.

Definition at line 88 of file imgproc/types_c.h.

Special filters.

Definition at line 94 of file imgproc/types_c.h.

Constants for color conversion.

Definition at line 101 of file imgproc/types_c.h.

Sub-pixel interpolation methods.

Definition at line 357 of file imgproc/types_c.h.

...

and other image warping flags

Definition at line 367 of file imgproc/types_c.h.

Morphological operations.

Definition at line 385 of file imgproc/types_c.h.

Template matching methods.

Definition at line 431 of file imgproc/types_c.h.

Contour retrieval modes.

Definition at line 444 of file imgproc/types_c.h.

Contour approximation methods.

Definition at line 454 of file imgproc/types_c.h.

Contour approximation algorithms.

Definition at line 489 of file imgproc/types_c.h.

Shape orientation.

Definition at line 510 of file imgproc/types_c.h.

Histogram comparison methods.

Definition at line 528 of file imgproc/types_c.h.

Mask size for distance transform.

Definition at line 540 of file imgproc/types_c.h.

Content of output label array: connected components or pixels.

Definition at line 548 of file imgproc/types_c.h.

Distance types for Distance Transform and M-estimators.

Enumerator:

CV_DIST_USER	User defined distance.
CV_DIST_L1	distance = |x1-x2| + |y1-y2|
CV_DIST_L2	the simple euclidean distance
CV_DIST_C	distance = max(|x1-x2|,|y1-y2|)
CV_DIST_L12	L1-L2 metric: distance = 2(sqrt(1+x*x/2) - 1))
CV_DIST_FAIR	distance = c^2(|x|/c-log(1+|x|/c)), c = 1.3998
CV_DIST_WELSCH	distance = c^2/2(1-exp(-(x/c)^2)), c = 2.9846
CV_DIST_HUBER	distance = |x|<c ? x^2/2 : c(|x|-c/2), c=1.345

Definition at line 555 of file imgproc/types_c.h.

Threshold types.

Enumerator:

CV_THRESH_BINARY	value = value > threshold ? max_value : 0
CV_THRESH_BINARY_INV	value = value > threshold ? 0 : max_value
CV_THRESH_TRUNC	value = value > threshold ? threshold : value
CV_THRESH_TOZERO	value = value > threshold ? value : 0
CV_THRESH_TOZERO_INV	value = value > threshold ? 0 : value
CV_THRESH_OTSU	use Otsu algorithm to choose the optimal threshold value; combine the flag with one of the above CV_THRESH_* values
CV_THRESH_TRIANGLE	use Triangle algorithm to choose the optimal threshold value; combine the flag with one of the above CV_THRESH_* values, but not with CV_THRESH_OTSU

Definition at line 569 of file imgproc/types_c.h.

Adaptive threshold methods.

Definition at line 585 of file imgproc/types_c.h.

FloodFill flags.

Definition at line 592 of file imgproc/types_c.h.

Canny edge detector flags.

Definition at line 600 of file imgproc/types_c.h.

Variants of a Hough transform.

Definition at line 606 of file imgproc/types_c.h.

Shapes of a structuring element for morphological operations.

See also:

cv::MorphShapes, cv::getStructuringElement

Enumerator:

CV_SHAPE_CUSTOM

custom structuring element

Definition at line 376 of file imgproc/types_c.h.

Shape matching methods.

denotes object1, denotes object2

and are the Hu moments of and , respectively.

Enumerator:

CV_CONTOURS_MATCH_I1
CV_CONTOURS_MATCH_I2
CV_CONTOURS_MATCH_I3

Definition at line 502 of file imgproc/types_c.h.

Image smooth methods.

Enumerator:

CV_BLUR_NO_SCALE	linear convolution with box kernel (all 1's). If you want to smooth different pixels with different-size box kernels, you can use the integral image that is computed using integral
CV_BLUR	linear convolution with box kernel (all 1's) with subsequent scaling by
CV_GAUSSIAN	linear convolution with a Gaussian kernel
CV_MEDIAN	median filter with a square aperture
CV_BILATERAL	bilateral filter with a square aperture, color sigma= sigma1 and spatial sigma= sigma2. If size1=0, the aperture square side is set to cvRound(sigma2\*1.5)\*2+1. See cv::bilateralFilter

Definition at line 68 of file imgproc/types_c.h.

Retrieves the next chain point.

See also:

cvApproxChains

Computes earth mover distance between two weighted point sets (called signatures)

See also:

cv::EMD

Unpacks color value.

if arrtype is CV_8UC?, _color_ is treated as packed color value, otherwise the first channels (depending on arrtype) of destination scalar are set to the same value = _color_

Fetches pixels that belong to the specified line segment and stores them to the buffer.

Returns the polygon points which make up the given ellipse.

Initializes line iterator.

Clips the line segment connecting *pt1 and *pt2 by the rectangular window.

Checks whether the contour is convex or not (returns 1 if convex, 0 if not)

Finds minimum enclosing circle for a set of points.

Retrieves outer and optionally inner boundaries of white (non-zero) connected components in the black (zero) background.

Returns the number of retrieved points.

See also:

cv::LineSegmentDetector

cv::findContours, cvStartFindContours, cvFindNextContour, cvSubstituteContour, cvEndFindContours

cv::minEnclosingCircle

cv::isContourConvex

(0<=x<img_size.width, 0<=y<img_size.height).

See also:

cv::clipLine

Initially, line_iterator->ptr will point to pt1 (or pt2, see left_to_right description) location in the image. Returns the number of pixels on the line between the ending points.

See also:

cv::LineIterator

The ellipse is define by the box of size 'axes' rotated 'angle' around the 'center'. A partial sweep of the ellipse arc can be done by spcifying arc_start and arc_end to be something other than 0 and 360, respectively. The input array 'pts' must be large enough to hold the result. The total number of points stored into 'pts' is returned by this function.

See also:

cv::ellipse2Poly

Adds image to accumulator.

Draws contour outlines or filled interiors on the image.

Calculates bounding box of text stroke (useful for alignment)

Renders text stroke with specified font and color at specified location.

Initializes font structure (OpenCV 1.x API).

Draws one or more polygonal curves.

Fills an area bounded by one or more arbitrary polygons.

Fills convex or monotonous polygon.

Draws ellipse outline, filled ellipse, elliptic arc or filled elliptic sector.

Draws a circle with specified center and radius.

Draws a rectangle specified by a CvRect structure.

Draws a rectangle given two opposite corners of the rectangle (pt1 & pt2)

Draws 4-connected, 8-connected or antialiased line segment connecting two points.

Fits a line into set of 2d or 3d points in a robust way (M-estimator technique)

Finds a sparse set of points within the selected region that seem to be easy to track.

Adjust corner position using some sort of gradient search.

Harris corner detector:

Calculates minimal eigenvalue for 2x2 gradient covariation matrix at every image pixel.

Calculates eigen values and vectors of 2x2 gradient covariation matrix at every image pixel.

Calculates constraint image for corner detection.

Runs canny edge detector.

Fills the connected component until the color difference gets large enough.

Applies adaptive threshold to grayscale image.

Applies distance transform to binary image.

equalizes histogram of 8-bit single-channel image

Divides one histogram by another.

Locates a template within an image by using a histogram comparison.

Calculates back project.

Calculates array histogram.

Calculates bayesian probabilistic histograms (each or src and dst is an array of _number_ histograms.

Copies a histogram.

Thresholds the histogram.

Normalizes the histogram.

Finds the minimum and maximum histogram bins.

Clears the histogram.

Releases the histogram.

Sets the bounds of the histogram bins.

Finds coordinates of the box vertices.

Initializes Freeman chain reader.

Substitutes the last retrieved contour with the new one.

Measures similarity between template and overlapped windows in the source image and fills the resultant image with the measurements.

Retrieves quadrangle from the input array.

Retrieves the rectangular image region with specified center from the input array.

Calculates 7 Hu's invariants from precalculated spatial and central moments.

Calculates all spatial and central moments up to the 3rd order.

Performs complex morphological transformation.

dilates input image (applies maximum filter) one or more times.

erodes input image (applies minimum filter) one or more times.

releases structuring element

Computes the original (undistorted) feature coordinates from the observed (distorted) coordinates.

Computes undistortion+rectification map for a head of stereo camera.

Computes transformation map from intrinsic camera parameters that can used by cvRemap.

Transforms the input image to compensate lens distortion.

Performs forward or inverse linear-polar image transform.

Performs forward or inverse log-polar image transform.

Converts mapx & mapy from floating-point to integer formats for cvRemap.

Performs generic geometric transformation using the specified coordinate maps.

Warps image with perspective (projective) transform.

Warps image with affine transform.

Resizes image (input array is resized to fit the destination array)

Converts input array pixels from one color space to another.

Calculates the image Laplacian: (d2/dx + d2/dy)I.

Calculates an image derivative using generalized Sobel.

Segments image using seed "markers".

Filters image using meanshift algorithm.

Releases pyramid.

Up-samples image and smoothes the result with gaussian kernel.

Smoothes the input image with gaussian kernel and then down-samples it.

Finds integral image: SUM(X,Y) = sum(x<X,y<Y)I(x,y)

Convolves an image with the kernel.

Smooths the image in one of several ways.

Copies source 2D array inside of the larger destination array and makes a border of the specified type (IPL_BORDER_*) around the copied area.

Adds image to accumulator with weights: acc = acc*(1-alpha) + image*alpha.

Adds a product of two images to accumulator.

Adds squared image to accumulator.

See also:

cv::accumulate

cv::accumulateSquare

cv::accumulateProduct

cv::accumulateWeighted

Parameters:

src	The source image
dst	The destination image
smoothtype	Type of the smoothing, see SmoothMethod_c
size1	The first parameter of the smoothing operation, the aperture width. Must be a positive odd number (1, 3, 5, ...)
size2	The second parameter of the smoothing operation, the aperture height. Ignored by CV_MEDIAN and CV_BILATERAL methods. In the case of simple scaled/non-scaled and Gaussian blur if size2 is zero, it is set to size1. Otherwise it must be a positive odd number.
sigma1	In the case of a Gaussian parameter this parameter may specify Gaussian (standard deviation). If it is zero, it is calculated from the kernel size: Using standard sigma for small kernels ( to ) gives better speed. If sigma1 is not zero, while size1 and size2 are zeros, the kernel size is calculated from the sigma (to provide accurate enough operation).
sigma2	additional parameter for bilateral filtering

See also:

cv::GaussianBlur, cv::blur, cv::medianBlur, cv::bilateralFilter.

Parameters:

src	input image.
dst	output image of the same size and the same number of channels as src.
kernel	convolution kernel (or rather a correlation kernel), a single-channel floating point matrix; if you want to apply different kernels to different channels, split the image into separate color planes using split and process them individually.
anchor	anchor of the kernel that indicates the relative position of a filtered point within the kernel; the anchor should lie within the kernel; default value (-1,-1) means that the anchor is at the kernel center.

See also:

cv::filter2D

cv::integral

dst_width = floor(src_width/2)[+1], dst_height = floor(src_height/2)[+1]

See also:

cv::pyrDown

dst_width = src_width*2, dst_height = src_height*2

See also:

cv::pyrUp

cv::pyrMeanShiftFiltering

cv::watershed

(aperture_size = 1,3,5,7) or Scharr (aperture_size = -1) operator. Scharr can be used only for the first dx or dy derivative

See also:

cv::Sobel

cv::Laplacian

cv::cvtColor

cv::resize

Note:

cvGetQuadrangleSubPix is similar to cvWarpAffine, but the outliers are extrapolated using replication border mode.

See also:

cv::warpAffine

cv::warpPerspective

cv::remap

cv::convertMaps

cv::logPolar

cv::linearPolar

cv::undistort

cv::initUndistortRectifyMap

cv::undistortPoints

cvCreateStructuringElementEx

If element pointer is NULL, 3x3 rectangular element is used

See also:

cv::erode

If element pointer is NULL, 3x3 rectangular element is used

See also:

cv::dilate

cv::morphologyEx

cv::moments

cv::HuMoments

dst(x,y) <- src(x + center.x - dst_width/2, y + center.y - dst_height/2). Values of pixels with fractional coordinates are retrieved using bilinear interpolation

See also:

cv::getRectSubPix

matrixarr = ( a11 a12 | b1 ) dst(x,y) <- src(A[x y]' + b) ( a21 a22 | b2 ) (bilinear interpolation is used to retrieve pixels with fractional coordinates)

See also:

cvWarpAffine

cv::matchTemplate

(if the substitutor is null, the last retrieved contour is removed from the tree)

See also:

cvFindContours

The reader is used to iteratively get coordinates of all the chain points. If the Freeman codes should be read as is, a simple sequence reader should be used

See also:

cvApproxChains

This is a standalone function for setting bin ranges in the histogram. For a more detailed description of the parameters ranges and uniform, see the :ocvCalcHist function that can initialize the ranges as well. Ranges for the histogram bins must be set before the histogram is calculated or the backproject of the histogram is calculated.

Parameters:

hist	Histogram.
ranges	Array of bin ranges arrays. See :ocvCreateHist for details.
uniform	Uniformity flag. See :ocvCreateHist for details.

The function releases the histogram (header and the data). The pointer to the histogram is cleared by the function. If \*hist pointer is already NULL, the function does nothing.

Parameters:

hist	Double pointer to the released histogram.

The function sets all of the histogram bins to 0 in case of a dense histogram and removes all histogram bins in case of a sparse array.

Parameters:

hist	Histogram.

The function finds the minimum and maximum histogram bins and their positions. All of output arguments are optional. Among several extremas with the same value the ones with the minimum index (in the lexicographical order) are returned. In case of several maximums or minimums, the earliest in the lexicographical order (extrema locations) is returned.

Parameters:

hist	Histogram.
min_value	Pointer to the minimum value of the histogram.
max_value	Pointer to the maximum value of the histogram.
min_idx	Pointer to the array of coordinates for the minimum.
max_idx	Pointer to the array of coordinates for the maximum.

The function normalizes the histogram bins by scaling them so that the sum of the bins becomes equal to factor.

Parameters:

hist	Pointer to the histogram.
factor	Normalization factor.

The function clears histogram bins that are below the specified threshold.

Parameters:

hist	Pointer to the histogram.
threshold	Threshold level.

The function makes a copy of the histogram. If the second histogram pointer \*dst is NULL, a new histogram of the same size as src is created. Otherwise, both histograms must have equal types and sizes. Then the function copies the bin values of the source histogram to the destination histogram and sets the same bin value ranges as in src.

Parameters:

src	Source histogram.
dst	Pointer to the destination histogram.

See also:

cv::calcHist

cvCalcBackProject, cv::calcBackProject

The function calculates the back projection by comparing histograms of the source image patches with the given histogram. The function is similar to matchTemplate, but instead of comparing the raster patch with all its possible positions within the search window, the function CalcBackProjectPatch compares histograms. See the algorithm diagram below:


Parameters:

image	Source images (though, you may pass CvMat\*\* as well).
dst	Destination image.
range
hist	Histogram.
method	Comparison method passed to cvCompareHist (see the function description).
factor	Normalization factor for histograms that affects the normalization scale of the destination image. Pass 1 if not sure.

See also:

cvCalcBackProjectPatch

The function calculates the object probability density from two histograms as:

Parameters:

hist1	First histogram (the divisor).
hist2	Second histogram.
dst_hist	Destination histogram.
scale	Scale factor for the destination histogram.

See also:

cv::equalizeHist

cv::distanceTransform

The two parameters for methods CV_ADAPTIVE_THRESH_MEAN_C and CV_ADAPTIVE_THRESH_GAUSSIAN_C are: neighborhood size (3, 5, 7 etc.), and a constant subtracted from mean (...,-3,-2,-1,0,1,2,3,...)

See also:

cv::adaptiveThreshold

cv::floodFill

cv::Canny

Dx^2 * Dyy + Dxx * Dy^2 - 2 * Dx * Dy * Dxy. Applying threshold to the result gives coordinates of corners

See also:

cv::preCornerDetect

cv::cornerEigenValsAndVecs

cv::cornerMinEigenVal

Calculates det(M) - k*(trace(M)^2), where M is 2x2 gradient covariation matrix for each pixel

See also:

cv::cornerHarris

cv::cornerSubPix

cv::goodFeaturesToTrack

cv::fitLine

cv::line

if thickness<0 (e.g. thickness == CV_FILLED), the filled box is drawn

See also:

cv::rectangle

cv::rectangle

Thickness works in the same way as with cvRectangle

See also:

cv::circle

depending on _thickness_, _start_angle_ and _end_angle_ parameters. The resultant figure is rotated by _angle_. All the angles are in degrees

See also:

cv::ellipse

cv::fillConvexPoly

cv::fillPoly

cv::polylines

The function initializes the font structure that can be passed to text rendering functions.

Parameters:

font	Pointer to the font structure initialized by the function
font_face	Font name identifier. See cv::HersheyFonts and corresponding old CV_* identifiers.
hscale	Horizontal scale. If equal to 1.0f , the characters have the original width depending on the font type. If equal to 0.5f , the characters are of half the original width.
vscale	Vertical scale. If equal to 1.0f , the characters have the original height depending on the font type. If equal to 0.5f , the characters are of half the original height.
shear	Approximate tangent of the character slope relative to the vertical line. A zero value means a non-italic font, 1.0f means about a 45 degree slope, etc.
thickness	Thickness of the text strokes
line_type	Type of the strokes, see line description

See also:

cvPutText

CvFont should be initialized with cvInitFont

See also:

cvInitFont, cvGetTextSize, cvFont, cv::putText

cv::getTextSize

cv::drawContours

Retrieve spatial moments.

Applies fixed-level threshold to grayscale image.

Compares two histogram.

Checks whether the point is inside polygon, outside, on an edge (at a vertex).

Compares two contours by matching their moments.

Calculates area of a contour or contour segment.

Calculates perimeter of a contour or length of a part of contour.

Retrieve normalized central moments.

Retrieve central moments.

See also:

cv::arcLength

cv::contourArea

cv::matchShapes

Returns positive, negative or zero value, correspondingly. Optionally, measures a signed distance between the point and the nearest polygon edge (measure_dist=1)

See also:

cv::pointPolygonTest

This is a basic operation applied before retrieving contours

See also:

cv::threshold

Initializes contour retrieving process.

Calls cvStartFindContours. Calls cvFindNextContour until null pointer is returned or some other condition becomes true. Calls cvEndFindContours at the end.

See also:

cvFindContours

Builds pyramid for an image.

See also:

buildPyramid

Finds minimum area rotated rectangle bounding a set of points.

Fits ellipse into a set of 2d points.

See also:

cv::minAreaRect

cv::fitEllipse

Computes affine transform matrix for mapping src[i] to dst[i] (i=0,1,2)

Computes perspective transform matrix for mapping src[i] to dst[i] (i=0,1,2,3)

Computes rotation_matrix matrix.

See also:

cv::getAffineTransform

cv::getRotationMatrix2D

cv::getPerspectiveTransform

Creates a histogram.

Makes a histogram out of an array.

The function creates a histogram of the specified size and returns a pointer to the created histogram. If the array ranges is 0, the histogram bin ranges must be specified later via the function cvSetHistBinRanges. Though cvCalcHist and cvCalcBackProject may process 8-bit images without setting bin ranges, they assume they are equally spaced in 0 to 255 bins.

Parameters:

dims	Number of histogram dimensions.
sizes	Array of the histogram dimension sizes.
type	Histogram representation format. CV_HIST_ARRAY means that the histogram data is represented as a multi-dimensional dense array CvMatND. CV_HIST_SPARSE means that histogram data is represented as a multi-dimensional sparse array CvSparseMat.
ranges	Array of ranges for the histogram bins. Its meaning depends on the uniform parameter value. The ranges are used when the histogram is calculated or backprojected to determine which histogram bin corresponds to which value/tuple of values from the input image(s).
uniform	Uniformity flag. If not zero, the histogram has evenly spaced bins and for every ranges[i] is an array of two numbers: lower and upper boundaries for the i-th histogram dimension. The whole range [lower,upper] is then split into dims[i] equal parts to determine the i-th input tuple value ranges for every histogram bin. And if uniform=0 , then the i-th element of the ranges array contains dims[i]+1 elements: where and are lower and upper boundaries of the i-th input tuple value for the j-th bin, respectively. In either case, the input values that are beyond the specified range for a histogram bin are not counted by cvCalcHist and filled with 0 by cvCalcBackProject.

The function initializes the histogram, whose header and bins are allocated by the user. cvReleaseHist does not need to be called afterwards. Only dense histograms can be initialized this way. The function returns hist.

Parameters:

dims	Number of the histogram dimensions.
sizes	Array of the histogram dimension sizes.
hist	Histogram header initialized by the function.
data	Array used to store histogram bins.
ranges	Histogram bin ranges. See cvCreateHist for details.
uniform	Uniformity flag. See cvCreateHist for details.

Calculates contour bounding rectangle (update=1) or just retrieves pre-calculated rectangle (update=0)

Finds minimum rectangle containing two given rectangles.

See also:

cv::boundingRect

Returns a structuring element of the specified size and shape for morphological operations.

Note:

the created structuring element IplConvKernel\* element must be released in the end using `cvReleaseStructuringElement(&element)`.

Parameters:

cols	Width of the structuring element
rows	Height of the structuring element
anchor_x	x-coordinate of the anchor
anchor_y	y-coordinate of the anchor
shape	element shape that could be one of the cv::MorphShapes_c
values	integer array of cols*rows elements that specifies the custom shape of the structuring element, when shape=CV_SHAPE_CUSTOM.

See also:

cv::getStructuringElement

Retrieves next contour.

Finds circles in the image.

Finds lines on binary image using one of several methods.

Initializes sequence header for a matrix (column or row vector) of points.

Finds convexity defects for the contour.

Calculates exact convex hull of 2d point set.

Approximates a single polygonal curve (contour) or a tree of polygonal curves (contours)

Approximates Freeman chain(s) with a polygonal curve.

Releases contour scanner and returns pointer to the first outer contour.

See also:

cvFindContours

This is a standalone contour approximation routine, not represented in the new interface. When cvFindContours retrieves contours as Freeman chains, it calls the function to get approximated contours, represented as polygons.

Parameters:

src_seq	Pointer to the approximated Freeman chain that can refer to other chains.
storage	Storage location for the resulting polylines.
method	Approximation method (see the description of the function :ocvFindContours ).
parameter	Method parameter (not used now).
minimal_perimeter	Approximates only those contours whose perimeters are not less than minimal_perimeter . Other chains are removed from the resulting structure.
recursive	Recursion flag. If it is non-zero, the function approximates all chains that can be obtained from chain by using the h_next or v_next links. Otherwise, the single input chain is approximated.

See also:

cvStartReadChainPoints, cvReadChainPoint

cv::approxPolyDP

cv::convexHull

cv::convexityDefects

a wrapper for cvMakeSeqHeaderForArray (it does not initialize bounding rectangle!!!)

line_storage is either memory storage or 1 x _max number of lines_ CvMat, its number of columns is changed by the function. method is one of CV_HOUGH_*; rho, theta and threshold are used for each of those methods; param1 ~ line length, param2 ~ line gap - for probabilistic, param1 ~ srn, param2 ~ stn - for multi-scale

See also:

cv::HoughLines

cv::HoughCircles

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Definition at line 771 of file imgproc_c.h.

same as cvArcLength for closed contour

Definition at line 530 of file imgproc_c.h.