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Fix typos.
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modules/imgproc/include/opencv2/imgproc.hpp

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@@ -416,7 +416,7 @@ enum ConnectedComponentsTypes {
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//! connected components algorithm
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enum ConnectedComponentsAlgorithmsTypes {
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CCL_WU = 0, //!< SAUF algorithm for 8-way connectivity, SAUF algorithm for 4-way connectivity
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CCL_DEFAULT = -1, //!< BBDT algortihm for 8-way connectivity, SAUF algorithm for 4-way connectivity
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CCL_DEFAULT = -1, //!< BBDT algorithm for 8-way connectivity, SAUF algorithm for 4-way connectivity
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CCL_GRANA = 1 //!< BBDT algorithm for 8-way connectivity, SAUF algorithm for 4-way connectivity
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};
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@@ -816,7 +816,7 @@ class CV_EXPORTS GeneralizedHough : public Algorithm
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};
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//! Ballard, D.H. (1981). Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13 (2): 111-122.
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//! Detects position only without traslation and rotation
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//! Detects position only without translation and rotation
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class CV_EXPORTS GeneralizedHoughBallard : public GeneralizedHough
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{
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public:
@@ -830,7 +830,7 @@ class CV_EXPORTS GeneralizedHoughBallard : public GeneralizedHough
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};
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//! Guil, N., González-Linares, J.M. and Zapata, E.L. (1999). Bidimensional shape detection using an invariant approach. Pattern Recognition 32 (6): 1025-1038.
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//! Detects position, traslation and rotation
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//! Detects position, translation and rotation
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class CV_EXPORTS GeneralizedHoughGuil : public GeneralizedHough
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{
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public:
@@ -985,7 +985,7 @@ class CV_EXPORTS_W Subdiv2D
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- The point is outside the subdivision reference rectangle. The function returns PTLOC_OUTSIDE_RECT
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and no pointers are filled.
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- One of input arguments is invalid. A runtime error is raised or, if silent or “parent” error
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processing mode is selected, CV_PTLOC_ERROR is returnd.
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processing mode is selected, CV_PTLOC_ERROR is returned.
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*/
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CV_WRAP int locate(Point2f pt, CV_OUT int& edge, CV_OUT int& vertex);
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@@ -1397,7 +1397,7 @@ CV_EXPORTS_W void bilateralFilter( InputArray src, OutputArray dst, int d,
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/** @brief Blurs an image using the box filter.
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The function smoothes an image using the kernel:
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The function smooths an image using the kernel:
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\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]
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@@ -1449,7 +1449,7 @@ CV_EXPORTS_W void sqrBoxFilter( InputArray _src, OutputArray _dst, int ddepth,
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/** @brief Blurs an image using the normalized box filter.
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The function smoothes an image using the kernel:
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The function smooths an image using the kernel:
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\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]
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@@ -3574,7 +3574,7 @@ CV_EXPORTS_W void cvtColor( InputArray src, OutputArray dst, int code, int dstCn
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//! @} imgproc_misc
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// main function for all demosaicing procceses
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// main function for all demosaicing processes
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CV_EXPORTS_W void demosaicing(InputArray _src, OutputArray _dst, int code, int dcn = 0);
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//! @addtogroup imgproc_shape
@@ -3756,7 +3756,7 @@ If mode equals to cv::RETR_CCOMP or cv::RETR_FLOODFILL, the input can also be a
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std::vector<std::vector<cv::Point> >).
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@param hierarchy Optional output vector (e.g. std::vector<cv::Vec4i>), containing information about the image topology. It has
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as many elements as the number of contours. For each i-th contour contours[i], the elements
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hierarchy[i][0] , hiearchy[i][1] , hiearchy[i][2] , and hiearchy[i][3] are set to 0-based indices
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hierarchy[i][0] , hierarchy[i][1] , hierarchy[i][2] , and hierarchy[i][3] are set to 0-based indices
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in contours of the next and previous contours at the same hierarchical level, the first child
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contour and the parent contour, respectively. If for the contour i there are no next, previous,
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parent, or nested contours, the corresponding elements of hierarchy[i] will be negative.
@@ -4044,7 +4044,7 @@ CV_EXPORTS_W double pointPolygonTest( InputArray contour, Point2f pt, bool measu
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/** @brief Finds out if there is any intersection between two rotated rectangles.
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If there is then the vertices of the interesecting region are returned as well.
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If there is then the vertices of the intersecting region are returned as well.
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Below are some examples of intersection configurations. The hatched pattern indicates the
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intersecting region and the red vertices are returned by the function.
@@ -4064,11 +4064,11 @@ CV_EXPORTS_W int rotatedRectangleIntersection( const RotatedRect& rect1, const R
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CV_EXPORTS_W Ptr<CLAHE> createCLAHE(double clipLimit = 40.0, Size tileGridSize = Size(8, 8));
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//! Ballard, D.H. (1981). Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13 (2): 111-122.
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//! Detects position only without traslation and rotation
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//! Detects position only without translation and rotation
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CV_EXPORTS Ptr<GeneralizedHoughBallard> createGeneralizedHoughBallard();
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//! Guil, N., González-Linares, J.M. and Zapata, E.L. (1999). Bidimensional shape detection using an invariant approach. Pattern Recognition 32 (6): 1025-1038.
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//! Detects position, traslation and rotation
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//! Detects position, translation and rotation
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CV_EXPORTS Ptr<GeneralizedHoughGuil> createGeneralizedHoughGuil();
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//! Performs linear blending of two images

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