//! connected components algorithm
enum ConnectedComponentsAlgorithmsTypes {
CCL_WU = 0, //!< SAUF algorithm for 8-way connectivity, SAUF algorithm for 4-way connectivity
- CCL_DEFAULT = -1, //!< BBDT algortihm for 8-way connectivity, SAUF algorithm for 4-way connectivity
+ CCL_DEFAULT = -1, //!< BBDT algorithm for 8-way connectivity, SAUF algorithm for 4-way connectivity
CCL_GRANA = 1 //!< BBDT algorithm for 8-way connectivity, SAUF algorithm for 4-way connectivity
};
CHAIN_APPROX_TC89_KCOS = 4
};
+/** @brief Shape matching methods
+
+\f$A\f$ denotes object1,\f$B\f$ denotes object2
+
+\f$\begin{array}{l} m^A_i = \mathrm{sign} (h^A_i) \cdot \log{h^A_i} \\ m^B_i = \mathrm{sign} (h^B_i) \cdot \log{h^B_i} \end{array}\f$
+
+and \f$h^A_i, h^B_i\f$ are the Hu moments of \f$A\f$ and \f$B\f$ , respectively.
+*/
+enum ShapeMatchModes {
+ CONTOURS_MATCH_I1 =1, //!< \f[I_1(A,B) = \sum _{i=1...7} \left | \frac{1}{m^A_i} - \frac{1}{m^B_i} \right |\f]
+ CONTOURS_MATCH_I2 =2, //!< \f[I_2(A,B) = \sum _{i=1...7} \left | m^A_i - m^B_i \right |\f]
+ CONTOURS_MATCH_I3 =3 //!< \f[I_3(A,B) = \max _{i=1...7} \frac{ \left| m^A_i - m^B_i \right| }{ \left| m^A_i \right| }\f]
+};
+
//! @} imgproc_shape
//! Variants of a Hough transform
};
//! 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
+//! Detects position only without translation and rotation
class CV_EXPORTS GeneralizedHoughBallard : public GeneralizedHough
{
public:
};
//! 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
+//! Detects position, translation and rotation
class CV_EXPORTS GeneralizedHoughGuil : public GeneralizedHough
{
public:
- The point is outside the subdivision reference rectangle. The function returns PTLOC_OUTSIDE_RECT
and no pointers are filled.
- One of input arguments is invalid. A runtime error is raised or, if silent or “parent” error
- processing mode is selected, CV_PTLOC_ERROR is returnd.
+ processing mode is selected, CV_PTLOC_ERROR is returned.
*/
CV_WRAP int locate(Point2f pt, CV_OUT int& edge, CV_OUT int& vertex);
You may also use the higher-level GaussianBlur.
@param ksize Aperture size. It should be odd ( \f$\texttt{ksize} \mod 2 = 1\f$ ) and positive.
@param sigma Gaussian standard deviation. If it is non-positive, it is computed from ksize as
-`sigma = 0.3\*((ksize-1)\*0.5 - 1) + 0.8`.
+`sigma = 0.3*((ksize-1)*0.5 - 1) + 0.8`.
@param ktype Type of filter coefficients. It can be CV_32F or CV_64F .
@sa sepFilter2D, getDerivKernels, getStructuringElement, GaussianBlur
*/
/** @brief Blurs an image using the box filter.
-The function smoothes an image using the kernel:
+The function smooths an image using the kernel:
\f[\texttt{K} = \alpha \begin{bmatrix} 1 & 1 & 1 & \cdots & 1 & 1 \\ 1 & 1 & 1 & \cdots & 1 & 1 \\ \hdotsfor{6} \\ 1 & 1 & 1 & \cdots & 1 & 1 \end{bmatrix}\f]
/** @brief Blurs an image using the normalized box filter.
-The function smoothes an image using the kernel:
+The function smooths an image using the kernel:
\f[\texttt{K} = \frac{1}{\texttt{ksize.width*ksize.height}} \begin{bmatrix} 1 & 1 & 1 & \cdots & 1 & 1 \\ 1 & 1 & 1 & \cdots & 1 & 1 \\ \hdotsfor{6} \\ 1 & 1 & 1 & \cdots & 1 & 1 \\ \end{bmatrix}\f]
The functions accumulate\* can be used, for example, to collect statistics of a scene background
viewed by a still camera and for the further foreground-background segmentation.
-@param src Input image as 1- or 3-channel, 8-bit or 32-bit floating point.
-@param dst %Accumulator image with the same number of channels as input image, 32-bit or 64-bit
-floating-point.
+@param src Input image of type CV_8UC(n), CV_16UC(n), CV_32FC(n) or CV_64FC(n), where n is a positive integer.
+@param dst %Accumulator image with the same number of channels as input image, and a depth of CV_32F or CV_64F.
@param mask Optional operation mask.
@sa accumulateSquare, accumulateProduct, accumulateWeighted
int distType, InputArray cost=noArray(),
float* lowerBound = 0, OutputArray flow = noArray() );
+CV_EXPORTS_AS(EMD) float wrapperEMD( InputArray signature1, InputArray signature2,
+ int distType, InputArray cost=noArray(),
+ CV_IN_OUT Ptr<float> lowerBound = Ptr<float>(), OutputArray flow = noArray() );
+
//! @} imgproc_hist
/** @example watershed.cpp
//! @} imgproc_misc
-// main function for all demosaicing procceses
+// main function for all demosaicing processes
CV_EXPORTS_W void demosaicing(InputArray _src, OutputArray _dst, int code, int dcn = 0);
//! @addtogroup imgproc_shape
is \f$W \times H\f$ and templ is \f$w \times h\f$ , then result is \f$(W-w+1) \times (H-h+1)\f$ .
@param method Parameter specifying the comparison method, see cv::TemplateMatchModes
@param mask Mask of searched template. It must have the same datatype and size with templ. It is
-not set by default.
+not set by default. Currently, only the TM_SQDIFF and TM_CCORR_NORMED methods are supported.
*/
CV_EXPORTS_W void matchTemplate( InputArray image, InputArray templ,
OutputArray result, int method, InputArray mask = noArray() );
std::vector<std::vector<cv::Point> >).
@param hierarchy Optional output vector (e.g. std::vector<cv::Vec4i>), containing information about the image topology. It has
as many elements as the number of contours. For each i-th contour contours[i], the elements
-hierarchy[i][0] , hiearchy[i][1] , hiearchy[i][2] , and hiearchy[i][3] are set to 0-based indices
+hierarchy[i][0] , hierarchy[i][1] , hierarchy[i][2] , and hierarchy[i][3] are set to 0-based indices
in contours of the next and previous contours at the same hierarchical level, the first child
contour and the parent contour, respectively. If for the contour i there are no next, previous,
parent, or nested contours, the corresponding elements of hierarchy[i] will be negative.
@param contour1 First contour or grayscale image.
@param contour2 Second contour or grayscale image.
-@param method Comparison method, see ::ShapeMatchModes
+@param method Comparison method, see cv::ShapeMatchModes
@param parameter Method-specific parameter (not supported now).
*/
CV_EXPORTS_W double matchShapes( InputArray contour1, InputArray contour2,
/** @brief Finds out if there is any intersection between two rotated rectangles.
-If there is then the vertices of the interesecting region are returned as well.
+If there is then the vertices of the intersecting region are returned as well.
Below are some examples of intersection configurations. The hatched pattern indicates the
intersecting region and the red vertices are returned by the function.
CV_EXPORTS_W Ptr<CLAHE> createCLAHE(double clipLimit = 40.0, Size tileGridSize = Size(8, 8));
//! 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
+//! Detects position only without translation and rotation
CV_EXPORTS Ptr<GeneralizedHoughBallard> createGeneralizedHoughBallard();
//! 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
+//! Detects position, translation and rotation
CV_EXPORTS Ptr<GeneralizedHoughGuil> createGeneralizedHoughGuil();
-//! Performs linear blending of two images
+//! Performs linear blending of two images:
+//! \f[ \texttt{dst}(i,j) = \texttt{weights1}(i,j)*\texttt{src1}(i,j) + \texttt{weights2}(i,j)*\texttt{src2}(i,j) \f]
+//! @param src1 It has a type of CV_8UC(n) or CV_32FC(n), where n is a positive integer.
+//! @param src2 It has the same type and size as src1.
+//! @param weights1 It has a type of CV_32FC1 and the same size with src1.
+//! @param weights2 It has a type of CV_32FC1 and the same size with src1.
+//! @param dst It is created if it does not have the same size and type with src1.
CV_EXPORTS void blendLinear(InputArray src1, InputArray src2, InputArray weights1, InputArray weights2, OutputArray dst);
//! @addtogroup imgproc_colormap
@param src The source image, grayscale or colored of type CV_8UC1 or CV_8UC3.
@param dst The result is the colormapped source image. Note: Mat::create is called on dst.
@param colormap The colormap to apply, see cv::ColormapTypes
- */
+*/
CV_EXPORTS_W void applyColorMap(InputArray src, OutputArray dst, int colormap);
+/** @brief Applies a user colormap on a given image.
+
+@param src The source image, grayscale or colored of type CV_8UC1 or CV_8UC3.
+@param dst The result is the colormapped source image. Note: Mat::create is called on dst.
+@param userColor The colormap to apply of type CV_8UC1 or CV_8UC3 and size 256
+*/
+CV_EXPORTS_W void applyColorMap(InputArray src, OutputArray dst, InputArray userColor);
+
//! @} imgproc_colormap
//! @addtogroup imgproc_draw
/** @brief Draws a simple or thick elliptic arc or fills an ellipse sector.
-The function cv::ellipse with less parameters draws an ellipse outline, a filled ellipse, an elliptic
-arc, or a filled ellipse sector. A piecewise-linear curve is used to approximate the elliptic arc
+The function cv::ellipse with more parameters draws an ellipse outline, a filled ellipse, an elliptic
+arc, or a filled ellipse sector. The drawing code uses general parametric form.
+A piecewise-linear curve is used to approximate the elliptic arc
boundary. If you need more control of the ellipse rendering, you can retrieve the curve using
-ellipse2Poly and then render it with polylines or fill it with fillPoly . If you use the first
-variant of the function and want to draw the whole ellipse, not an arc, pass startAngle=0 and
-endAngle=360 . The figure below explains the meaning of the parameters.
+cv::ellipse2Poly and then render it with polylines or fill it with cv::fillPoly. If you use the first
+variant of the function and want to draw the whole ellipse, not an arc, pass `startAngle=0` and
+`endAngle=360`. If `startAngle` is greater than `endAngle`, they are swapped. The figure below explains
+the meaning of the parameters to draw the blue arc.
-
+
@param img Image.
@param center Center of the ellipse.
/** @brief Approximates an elliptic arc with a polyline.
The function ellipse2Poly computes the vertices of a polyline that approximates the specified
-elliptic arc. It is used by cv::ellipse.
+elliptic arc. It is used by cv::ellipse. If `arcStart` is greater than `arcEnd`, they are swapped.
@param center Center of the arc.
@param axes Half of the size of the ellipse main axes. See the ellipse for details.
projects / platform / upstream / opencv.git / blobdiff