627 lines
17 KiB
C
627 lines
17 KiB
C
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#ifndef __OPENCV_IMGPROC_TYPES_C_H__
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#define __OPENCV_IMGPROC_TYPES_C_H__
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#include "opencv2/core/core_c.h"
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#ifdef __cplusplus
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extern "C" {
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#endif
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/** @addtogroup imgproc_c
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@{
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*/
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/** Connected component structure */
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typedef struct CvConnectedComp
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{
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double area; /**<area of the connected component */
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CvScalar value; /**<average color of the connected component */
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CvRect rect; /**<ROI of the component */
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CvSeq* contour; /**<optional component boundary
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(the contour might have child contours corresponding to the holes)*/
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}
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CvConnectedComp;
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/** Image smooth methods */
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enum SmoothMethod_c
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{
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/** linear convolution with \f$\texttt{size1}\times\texttt{size2}\f$ box kernel (all 1's). If
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you want to smooth different pixels with different-size box kernels, you can use the integral
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image that is computed using integral */
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CV_BLUR_NO_SCALE =0,
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/** linear convolution with \f$\texttt{size1}\times\texttt{size2}\f$ box kernel (all
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1's) with subsequent scaling by \f$1/(\texttt{size1}\cdot\texttt{size2})\f$ */
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CV_BLUR =1,
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/** linear convolution with a \f$\texttt{size1}\times\texttt{size2}\f$ Gaussian kernel */
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CV_GAUSSIAN =2,
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/** median filter with a \f$\texttt{size1}\times\texttt{size1}\f$ square aperture */
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CV_MEDIAN =3,
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/** bilateral filter with a \f$\texttt{size1}\times\texttt{size1}\f$ square aperture, color
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sigma= sigma1 and spatial sigma= sigma2. If size1=0, the aperture square side is set to
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cvRound(sigma2\*1.5)\*2+1. See cv::bilateralFilter */
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CV_BILATERAL =4
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};
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/** Filters used in pyramid decomposition */
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enum
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{
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CV_GAUSSIAN_5x5 = 7
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};
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/** Special filters */
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enum
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{
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CV_SCHARR =-1,
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CV_MAX_SOBEL_KSIZE =7
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};
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/** Constants for color conversion */
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enum
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{
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CV_BGR2BGRA =0,
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CV_RGB2RGBA =CV_BGR2BGRA,
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CV_BGRA2BGR =1,
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CV_RGBA2RGB =CV_BGRA2BGR,
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CV_BGR2RGBA =2,
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CV_RGB2BGRA =CV_BGR2RGBA,
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CV_RGBA2BGR =3,
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CV_BGRA2RGB =CV_RGBA2BGR,
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CV_BGR2RGB =4,
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CV_RGB2BGR =CV_BGR2RGB,
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CV_BGRA2RGBA =5,
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CV_RGBA2BGRA =CV_BGRA2RGBA,
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CV_BGR2GRAY =6,
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CV_RGB2GRAY =7,
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CV_GRAY2BGR =8,
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CV_GRAY2RGB =CV_GRAY2BGR,
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CV_GRAY2BGRA =9,
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CV_GRAY2RGBA =CV_GRAY2BGRA,
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CV_BGRA2GRAY =10,
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CV_RGBA2GRAY =11,
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CV_BGR2BGR565 =12,
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CV_RGB2BGR565 =13,
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CV_BGR5652BGR =14,
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CV_BGR5652RGB =15,
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CV_BGRA2BGR565 =16,
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CV_RGBA2BGR565 =17,
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CV_BGR5652BGRA =18,
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CV_BGR5652RGBA =19,
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CV_GRAY2BGR565 =20,
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CV_BGR5652GRAY =21,
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CV_BGR2BGR555 =22,
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CV_RGB2BGR555 =23,
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CV_BGR5552BGR =24,
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CV_BGR5552RGB =25,
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CV_BGRA2BGR555 =26,
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CV_RGBA2BGR555 =27,
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CV_BGR5552BGRA =28,
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CV_BGR5552RGBA =29,
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CV_GRAY2BGR555 =30,
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CV_BGR5552GRAY =31,
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CV_BGR2XYZ =32,
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CV_RGB2XYZ =33,
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CV_XYZ2BGR =34,
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CV_XYZ2RGB =35,
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CV_BGR2YCrCb =36,
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CV_RGB2YCrCb =37,
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CV_YCrCb2BGR =38,
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CV_YCrCb2RGB =39,
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CV_BGR2HSV =40,
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CV_RGB2HSV =41,
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CV_BGR2Lab =44,
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CV_RGB2Lab =45,
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CV_BayerBG2BGR =46,
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CV_BayerGB2BGR =47,
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CV_BayerRG2BGR =48,
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CV_BayerGR2BGR =49,
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CV_BayerBG2RGB =CV_BayerRG2BGR,
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CV_BayerGB2RGB =CV_BayerGR2BGR,
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CV_BayerRG2RGB =CV_BayerBG2BGR,
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CV_BayerGR2RGB =CV_BayerGB2BGR,
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CV_BGR2Luv =50,
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CV_RGB2Luv =51,
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CV_BGR2HLS =52,
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CV_RGB2HLS =53,
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CV_HSV2BGR =54,
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CV_HSV2RGB =55,
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CV_Lab2BGR =56,
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CV_Lab2RGB =57,
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CV_Luv2BGR =58,
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CV_Luv2RGB =59,
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CV_HLS2BGR =60,
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CV_HLS2RGB =61,
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CV_BayerBG2BGR_VNG =62,
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CV_BayerGB2BGR_VNG =63,
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CV_BayerRG2BGR_VNG =64,
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CV_BayerGR2BGR_VNG =65,
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CV_BayerBG2RGB_VNG =CV_BayerRG2BGR_VNG,
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CV_BayerGB2RGB_VNG =CV_BayerGR2BGR_VNG,
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CV_BayerRG2RGB_VNG =CV_BayerBG2BGR_VNG,
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CV_BayerGR2RGB_VNG =CV_BayerGB2BGR_VNG,
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CV_BGR2HSV_FULL = 66,
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CV_RGB2HSV_FULL = 67,
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CV_BGR2HLS_FULL = 68,
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CV_RGB2HLS_FULL = 69,
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CV_HSV2BGR_FULL = 70,
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CV_HSV2RGB_FULL = 71,
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CV_HLS2BGR_FULL = 72,
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CV_HLS2RGB_FULL = 73,
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CV_LBGR2Lab = 74,
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CV_LRGB2Lab = 75,
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CV_LBGR2Luv = 76,
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CV_LRGB2Luv = 77,
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CV_Lab2LBGR = 78,
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CV_Lab2LRGB = 79,
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CV_Luv2LBGR = 80,
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CV_Luv2LRGB = 81,
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CV_BGR2YUV = 82,
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CV_RGB2YUV = 83,
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CV_YUV2BGR = 84,
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CV_YUV2RGB = 85,
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CV_BayerBG2GRAY = 86,
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CV_BayerGB2GRAY = 87,
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CV_BayerRG2GRAY = 88,
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CV_BayerGR2GRAY = 89,
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//YUV 4:2:0 formats family
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CV_YUV2RGB_NV12 = 90,
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CV_YUV2BGR_NV12 = 91,
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CV_YUV2RGB_NV21 = 92,
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CV_YUV2BGR_NV21 = 93,
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CV_YUV420sp2RGB = CV_YUV2RGB_NV21,
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CV_YUV420sp2BGR = CV_YUV2BGR_NV21,
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CV_YUV2RGBA_NV12 = 94,
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CV_YUV2BGRA_NV12 = 95,
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CV_YUV2RGBA_NV21 = 96,
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CV_YUV2BGRA_NV21 = 97,
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CV_YUV420sp2RGBA = CV_YUV2RGBA_NV21,
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CV_YUV420sp2BGRA = CV_YUV2BGRA_NV21,
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CV_YUV2RGB_YV12 = 98,
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CV_YUV2BGR_YV12 = 99,
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CV_YUV2RGB_IYUV = 100,
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CV_YUV2BGR_IYUV = 101,
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CV_YUV2RGB_I420 = CV_YUV2RGB_IYUV,
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CV_YUV2BGR_I420 = CV_YUV2BGR_IYUV,
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CV_YUV420p2RGB = CV_YUV2RGB_YV12,
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CV_YUV420p2BGR = CV_YUV2BGR_YV12,
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CV_YUV2RGBA_YV12 = 102,
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CV_YUV2BGRA_YV12 = 103,
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CV_YUV2RGBA_IYUV = 104,
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CV_YUV2BGRA_IYUV = 105,
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CV_YUV2RGBA_I420 = CV_YUV2RGBA_IYUV,
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CV_YUV2BGRA_I420 = CV_YUV2BGRA_IYUV,
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CV_YUV420p2RGBA = CV_YUV2RGBA_YV12,
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CV_YUV420p2BGRA = CV_YUV2BGRA_YV12,
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CV_YUV2GRAY_420 = 106,
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CV_YUV2GRAY_NV21 = CV_YUV2GRAY_420,
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CV_YUV2GRAY_NV12 = CV_YUV2GRAY_420,
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CV_YUV2GRAY_YV12 = CV_YUV2GRAY_420,
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CV_YUV2GRAY_IYUV = CV_YUV2GRAY_420,
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CV_YUV2GRAY_I420 = CV_YUV2GRAY_420,
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CV_YUV420sp2GRAY = CV_YUV2GRAY_420,
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CV_YUV420p2GRAY = CV_YUV2GRAY_420,
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//YUV 4:2:2 formats family
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CV_YUV2RGB_UYVY = 107,
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CV_YUV2BGR_UYVY = 108,
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//CV_YUV2RGB_VYUY = 109,
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//CV_YUV2BGR_VYUY = 110,
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CV_YUV2RGB_Y422 = CV_YUV2RGB_UYVY,
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CV_YUV2BGR_Y422 = CV_YUV2BGR_UYVY,
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CV_YUV2RGB_UYNV = CV_YUV2RGB_UYVY,
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CV_YUV2BGR_UYNV = CV_YUV2BGR_UYVY,
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CV_YUV2RGBA_UYVY = 111,
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CV_YUV2BGRA_UYVY = 112,
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//CV_YUV2RGBA_VYUY = 113,
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//CV_YUV2BGRA_VYUY = 114,
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CV_YUV2RGBA_Y422 = CV_YUV2RGBA_UYVY,
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CV_YUV2BGRA_Y422 = CV_YUV2BGRA_UYVY,
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CV_YUV2RGBA_UYNV = CV_YUV2RGBA_UYVY,
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CV_YUV2BGRA_UYNV = CV_YUV2BGRA_UYVY,
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CV_YUV2RGB_YUY2 = 115,
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CV_YUV2BGR_YUY2 = 116,
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CV_YUV2RGB_YVYU = 117,
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CV_YUV2BGR_YVYU = 118,
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CV_YUV2RGB_YUYV = CV_YUV2RGB_YUY2,
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CV_YUV2BGR_YUYV = CV_YUV2BGR_YUY2,
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CV_YUV2RGB_YUNV = CV_YUV2RGB_YUY2,
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CV_YUV2BGR_YUNV = CV_YUV2BGR_YUY2,
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CV_YUV2RGBA_YUY2 = 119,
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CV_YUV2BGRA_YUY2 = 120,
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CV_YUV2RGBA_YVYU = 121,
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CV_YUV2BGRA_YVYU = 122,
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CV_YUV2RGBA_YUYV = CV_YUV2RGBA_YUY2,
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CV_YUV2BGRA_YUYV = CV_YUV2BGRA_YUY2,
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CV_YUV2RGBA_YUNV = CV_YUV2RGBA_YUY2,
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CV_YUV2BGRA_YUNV = CV_YUV2BGRA_YUY2,
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CV_YUV2GRAY_UYVY = 123,
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CV_YUV2GRAY_YUY2 = 124,
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//CV_YUV2GRAY_VYUY = CV_YUV2GRAY_UYVY,
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CV_YUV2GRAY_Y422 = CV_YUV2GRAY_UYVY,
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CV_YUV2GRAY_UYNV = CV_YUV2GRAY_UYVY,
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CV_YUV2GRAY_YVYU = CV_YUV2GRAY_YUY2,
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CV_YUV2GRAY_YUYV = CV_YUV2GRAY_YUY2,
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CV_YUV2GRAY_YUNV = CV_YUV2GRAY_YUY2,
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// alpha premultiplication
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CV_RGBA2mRGBA = 125,
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CV_mRGBA2RGBA = 126,
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CV_RGB2YUV_I420 = 127,
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CV_BGR2YUV_I420 = 128,
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CV_RGB2YUV_IYUV = CV_RGB2YUV_I420,
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CV_BGR2YUV_IYUV = CV_BGR2YUV_I420,
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CV_RGBA2YUV_I420 = 129,
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CV_BGRA2YUV_I420 = 130,
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CV_RGBA2YUV_IYUV = CV_RGBA2YUV_I420,
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CV_BGRA2YUV_IYUV = CV_BGRA2YUV_I420,
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CV_RGB2YUV_YV12 = 131,
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CV_BGR2YUV_YV12 = 132,
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CV_RGBA2YUV_YV12 = 133,
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CV_BGRA2YUV_YV12 = 134,
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// Edge-Aware Demosaicing
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CV_BayerBG2BGR_EA = 135,
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CV_BayerGB2BGR_EA = 136,
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CV_BayerRG2BGR_EA = 137,
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CV_BayerGR2BGR_EA = 138,
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CV_BayerBG2RGB_EA = CV_BayerRG2BGR_EA,
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CV_BayerGB2RGB_EA = CV_BayerGR2BGR_EA,
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CV_BayerRG2RGB_EA = CV_BayerBG2BGR_EA,
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CV_BayerGR2RGB_EA = CV_BayerGB2BGR_EA,
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CV_COLORCVT_MAX = 139
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};
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/** Sub-pixel interpolation methods */
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enum
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{
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CV_INTER_NN =0,
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CV_INTER_LINEAR =1,
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CV_INTER_CUBIC =2,
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CV_INTER_AREA =3,
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CV_INTER_LANCZOS4 =4
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};
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/** ... and other image warping flags */
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enum
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{
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CV_WARP_FILL_OUTLIERS =8,
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CV_WARP_INVERSE_MAP =16
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};
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/** Shapes of a structuring element for morphological operations
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@see cv::MorphShapes, cv::getStructuringElement
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*/
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enum MorphShapes_c
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{
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CV_SHAPE_RECT =0,
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CV_SHAPE_CROSS =1,
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CV_SHAPE_ELLIPSE =2,
|
||
|
CV_SHAPE_CUSTOM =100 //!< custom structuring element
|
||
|
};
|
||
|
|
||
|
/** Morphological operations */
|
||
|
enum
|
||
|
{
|
||
|
CV_MOP_ERODE =0,
|
||
|
CV_MOP_DILATE =1,
|
||
|
CV_MOP_OPEN =2,
|
||
|
CV_MOP_CLOSE =3,
|
||
|
CV_MOP_GRADIENT =4,
|
||
|
CV_MOP_TOPHAT =5,
|
||
|
CV_MOP_BLACKHAT =6
|
||
|
};
|
||
|
|
||
|
/** Spatial and central moments */
|
||
|
typedef struct CvMoments
|
||
|
{
|
||
|
double m00, m10, m01, m20, m11, m02, m30, m21, m12, m03; /**< spatial moments */
|
||
|
double mu20, mu11, mu02, mu30, mu21, mu12, mu03; /**< central moments */
|
||
|
double inv_sqrt_m00; /**< m00 != 0 ? 1/sqrt(m00) : 0 */
|
||
|
|
||
|
#ifdef __cplusplus
|
||
|
CvMoments(){}
|
||
|
CvMoments(const cv::Moments& m)
|
||
|
{
|
||
|
m00 = m.m00; m10 = m.m10; m01 = m.m01;
|
||
|
m20 = m.m20; m11 = m.m11; m02 = m.m02;
|
||
|
m30 = m.m30; m21 = m.m21; m12 = m.m12; m03 = m.m03;
|
||
|
mu20 = m.mu20; mu11 = m.mu11; mu02 = m.mu02;
|
||
|
mu30 = m.mu30; mu21 = m.mu21; mu12 = m.mu12; mu03 = m.mu03;
|
||
|
double am00 = std::abs(m.m00);
|
||
|
inv_sqrt_m00 = am00 > DBL_EPSILON ? 1./std::sqrt(am00) : 0;
|
||
|
}
|
||
|
operator cv::Moments() const
|
||
|
{
|
||
|
return cv::Moments(m00, m10, m01, m20, m11, m02, m30, m21, m12, m03);
|
||
|
}
|
||
|
#endif
|
||
|
}
|
||
|
CvMoments;
|
||
|
|
||
|
/** Hu invariants */
|
||
|
typedef struct CvHuMoments
|
||
|
{
|
||
|
double hu1, hu2, hu3, hu4, hu5, hu6, hu7; /**< Hu invariants */
|
||
|
}
|
||
|
CvHuMoments;
|
||
|
|
||
|
/** Template matching methods */
|
||
|
enum
|
||
|
{
|
||
|
CV_TM_SQDIFF =0,
|
||
|
CV_TM_SQDIFF_NORMED =1,
|
||
|
CV_TM_CCORR =2,
|
||
|
CV_TM_CCORR_NORMED =3,
|
||
|
CV_TM_CCOEFF =4,
|
||
|
CV_TM_CCOEFF_NORMED =5
|
||
|
};
|
||
|
|
||
|
typedef float (CV_CDECL * CvDistanceFunction)( const float* a, const float* b, void* user_param );
|
||
|
|
||
|
/** Contour retrieval modes */
|
||
|
enum
|
||
|
{
|
||
|
CV_RETR_EXTERNAL=0,
|
||
|
CV_RETR_LIST=1,
|
||
|
CV_RETR_CCOMP=2,
|
||
|
CV_RETR_TREE=3,
|
||
|
CV_RETR_FLOODFILL=4
|
||
|
};
|
||
|
|
||
|
/** Contour approximation methods */
|
||
|
enum
|
||
|
{
|
||
|
CV_CHAIN_CODE=0,
|
||
|
CV_CHAIN_APPROX_NONE=1,
|
||
|
CV_CHAIN_APPROX_SIMPLE=2,
|
||
|
CV_CHAIN_APPROX_TC89_L1=3,
|
||
|
CV_CHAIN_APPROX_TC89_KCOS=4,
|
||
|
CV_LINK_RUNS=5
|
||
|
};
|
||
|
|
||
|
/*
|
||
|
Internal structure that is used for sequential retrieving contours from the image.
|
||
|
It supports both hierarchical and plane variants of Suzuki algorithm.
|
||
|
*/
|
||
|
typedef struct _CvContourScanner* CvContourScanner;
|
||
|
|
||
|
/** Freeman chain reader state */
|
||
|
typedef struct CvChainPtReader
|
||
|
{
|
||
|
CV_SEQ_READER_FIELDS()
|
||
|
char code;
|
||
|
CvPoint pt;
|
||
|
schar deltas[8][2];
|
||
|
}
|
||
|
CvChainPtReader;
|
||
|
|
||
|
/** initializes 8-element array for fast access to 3x3 neighborhood of a pixel */
|
||
|
#define CV_INIT_3X3_DELTAS( deltas, step, nch ) \
|
||
|
((deltas)[0] = (nch), (deltas)[1] = -(step) + (nch), \
|
||
|
(deltas)[2] = -(step), (deltas)[3] = -(step) - (nch), \
|
||
|
(deltas)[4] = -(nch), (deltas)[5] = (step) - (nch), \
|
||
|
(deltas)[6] = (step), (deltas)[7] = (step) + (nch))
|
||
|
|
||
|
|
||
|
/** Contour approximation algorithms */
|
||
|
enum
|
||
|
{
|
||
|
CV_POLY_APPROX_DP = 0
|
||
|
};
|
||
|
|
||
|
/** @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
|
||
|
{
|
||
|
CV_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]
|
||
|
CV_CONTOURS_MATCH_I2 =2, //!< \f[I_2(A,B) = \sum _{i=1...7} \left | m^A_i - m^B_i \right |\f]
|
||
|
CV_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]
|
||
|
};
|
||
|
|
||
|
/** Shape orientation */
|
||
|
enum
|
||
|
{
|
||
|
CV_CLOCKWISE =1,
|
||
|
CV_COUNTER_CLOCKWISE =2
|
||
|
};
|
||
|
|
||
|
|
||
|
/** Convexity defect */
|
||
|
typedef struct CvConvexityDefect
|
||
|
{
|
||
|
CvPoint* start; /**< point of the contour where the defect begins */
|
||
|
CvPoint* end; /**< point of the contour where the defect ends */
|
||
|
CvPoint* depth_point; /**< the farthest from the convex hull point within the defect */
|
||
|
float depth; /**< distance between the farthest point and the convex hull */
|
||
|
} CvConvexityDefect;
|
||
|
|
||
|
|
||
|
/** Histogram comparison methods */
|
||
|
enum
|
||
|
{
|
||
|
CV_COMP_CORREL =0,
|
||
|
CV_COMP_CHISQR =1,
|
||
|
CV_COMP_INTERSECT =2,
|
||
|
CV_COMP_BHATTACHARYYA =3,
|
||
|
CV_COMP_HELLINGER =CV_COMP_BHATTACHARYYA,
|
||
|
CV_COMP_CHISQR_ALT =4,
|
||
|
CV_COMP_KL_DIV =5
|
||
|
};
|
||
|
|
||
|
/** Mask size for distance transform */
|
||
|
enum
|
||
|
{
|
||
|
CV_DIST_MASK_3 =3,
|
||
|
CV_DIST_MASK_5 =5,
|
||
|
CV_DIST_MASK_PRECISE =0
|
||
|
};
|
||
|
|
||
|
/** Content of output label array: connected components or pixels */
|
||
|
enum
|
||
|
{
|
||
|
CV_DIST_LABEL_CCOMP = 0,
|
||
|
CV_DIST_LABEL_PIXEL = 1
|
||
|
};
|
||
|
|
||
|
/** Distance types for Distance Transform and M-estimators */
|
||
|
enum
|
||
|
{
|
||
|
CV_DIST_USER =-1, /**< User defined distance */
|
||
|
CV_DIST_L1 =1, /**< distance = |x1-x2| + |y1-y2| */
|
||
|
CV_DIST_L2 =2, /**< the simple euclidean distance */
|
||
|
CV_DIST_C =3, /**< distance = max(|x1-x2|,|y1-y2|) */
|
||
|
CV_DIST_L12 =4, /**< L1-L2 metric: distance = 2(sqrt(1+x*x/2) - 1)) */
|
||
|
CV_DIST_FAIR =5, /**< distance = c^2(|x|/c-log(1+|x|/c)), c = 1.3998 */
|
||
|
CV_DIST_WELSCH =6, /**< distance = c^2/2(1-exp(-(x/c)^2)), c = 2.9846 */
|
||
|
CV_DIST_HUBER =7 /**< distance = |x|<c ? x^2/2 : c(|x|-c/2), c=1.345 */
|
||
|
};
|
||
|
|
||
|
|
||
|
/** Threshold types */
|
||
|
enum
|
||
|
{
|
||
|
CV_THRESH_BINARY =0, /**< value = value > threshold ? max_value : 0 */
|
||
|
CV_THRESH_BINARY_INV =1, /**< value = value > threshold ? 0 : max_value */
|
||
|
CV_THRESH_TRUNC =2, /**< value = value > threshold ? threshold : value */
|
||
|
CV_THRESH_TOZERO =3, /**< value = value > threshold ? value : 0 */
|
||
|
CV_THRESH_TOZERO_INV =4, /**< value = value > threshold ? 0 : value */
|
||
|
CV_THRESH_MASK =7,
|
||
|
CV_THRESH_OTSU =8, /**< use Otsu algorithm to choose the optimal threshold value;
|
||
|
combine the flag with one of the above CV_THRESH_* values */
|
||
|
CV_THRESH_TRIANGLE =16 /**< 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 */
|
||
|
};
|
||
|
|
||
|
/** Adaptive threshold methods */
|
||
|
enum
|
||
|
{
|
||
|
CV_ADAPTIVE_THRESH_MEAN_C =0,
|
||
|
CV_ADAPTIVE_THRESH_GAUSSIAN_C =1
|
||
|
};
|
||
|
|
||
|
/** FloodFill flags */
|
||
|
enum
|
||
|
{
|
||
|
CV_FLOODFILL_FIXED_RANGE =(1 << 16),
|
||
|
CV_FLOODFILL_MASK_ONLY =(1 << 17)
|
||
|
};
|
||
|
|
||
|
|
||
|
/** Canny edge detector flags */
|
||
|
enum
|
||
|
{
|
||
|
CV_CANNY_L2_GRADIENT =(1 << 31)
|
||
|
};
|
||
|
|
||
|
/** Variants of a Hough transform */
|
||
|
enum
|
||
|
{
|
||
|
CV_HOUGH_STANDARD =0,
|
||
|
CV_HOUGH_PROBABILISTIC =1,
|
||
|
CV_HOUGH_MULTI_SCALE =2,
|
||
|
CV_HOUGH_GRADIENT =3
|
||
|
};
|
||
|
|
||
|
|
||
|
/* Fast search data structures */
|
||
|
struct CvFeatureTree;
|
||
|
struct CvLSH;
|
||
|
struct CvLSHOperations;
|
||
|
|
||
|
/** @} */
|
||
|
|
||
|
#ifdef __cplusplus
|
||
|
}
|
||
|
#endif
|
||
|
|
||
|
#endif
|