/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #ifndef OPENCV_IMGPROC_TYPES_C_H #define OPENCV_IMGPROC_TYPES_C_H #include "opencv2/core/core_c.h" #ifdef __cplusplus extern "C" { #endif /** @addtogroup imgproc_c @{ */ /** Connected component structure */ typedef struct CvConnectedComp { double area; /** 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 }; /** Shape matching methods */ enum { 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| 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