+++ /dev/null
-/*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.
-//
-//
-// Intel License Agreement
-// For Open Source Computer Vision Library
-//
-// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 _CVTYPES_H_
-#define _CVTYPES_H_
-
-#ifndef SKIP_INCLUDES
- #include <assert.h>
- #include <stdlib.h>
-#endif
-
-/* 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 */
-}
-CvMoments;
-
-/* Hu invariants */
-typedef struct CvHuMoments
-{
- double hu1, hu2, hu3, hu4, hu5, hu6, hu7; /* Hu invariants */
-}
-CvHuMoments;
-
-/**************************** Connected Component **************************************/
-
-typedef struct CvConnectedComp
-{
- double area; /* area of the connected component */
- CvScalar value; /* average color of the connected component */
- CvRect rect; /* ROI of the component */
- CvSeq* contour; /* optional component boundary
- (the contour might have child contours corresponding to the holes)*/
-}
-CvConnectedComp;
-
-/*
-Internal structure that is used for sequental retrieving contours from the image.
-It supports both hierarchical and plane variants of Suzuki algorithm.
-*/
-typedef struct _CvContourScanner* CvContourScanner;
-
-/* contour retrieval mode */
-#define CV_RETR_EXTERNAL 0
-#define CV_RETR_LIST 1
-#define CV_RETR_CCOMP 2
-#define CV_RETR_TREE 3
-
-/* contour approximation method */
-#define CV_CHAIN_CODE 0
-#define CV_CHAIN_APPROX_NONE 1
-#define CV_CHAIN_APPROX_SIMPLE 2
-#define CV_CHAIN_APPROX_TC89_L1 3
-#define CV_CHAIN_APPROX_TC89_KCOS 4
-#define CV_LINK_RUNS 5
-
-/* 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 tree header */
-typedef struct CvContourTree
-{
- CV_SEQUENCE_FIELDS()
- CvPoint p1; /* the first point of the binary tree root segment */
- CvPoint p2; /* the last point of the binary tree root segment */
-}
-CvContourTree;
-
-/* Finds a sequence of convexity defects of given contour */
-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;
-
-/************ Data structures and related enumerations for Planar Subdivisions ************/
-
-typedef size_t CvSubdiv2DEdge;
-
-#define CV_QUADEDGE2D_FIELDS() \
- int flags; \
- struct CvSubdiv2DPoint* pt[4]; \
- CvSubdiv2DEdge next[4];
-
-#define CV_SUBDIV2D_POINT_FIELDS()\
- int flags; \
- CvSubdiv2DEdge first; \
- CvPoint2D32f pt;
-
-#define CV_SUBDIV2D_VIRTUAL_POINT_FLAG (1 << 30)
-
-typedef struct CvQuadEdge2D
-{
- CV_QUADEDGE2D_FIELDS()
-}
-CvQuadEdge2D;
-
-typedef struct CvSubdiv2DPoint
-{
- CV_SUBDIV2D_POINT_FIELDS()
-}
-CvSubdiv2DPoint;
-
-#define CV_SUBDIV2D_FIELDS() \
- CV_GRAPH_FIELDS() \
- int quad_edges; \
- int is_geometry_valid; \
- CvSubdiv2DEdge recent_edge; \
- CvPoint2D32f topleft; \
- CvPoint2D32f bottomright;
-
-typedef struct CvSubdiv2D
-{
- CV_SUBDIV2D_FIELDS()
-}
-CvSubdiv2D;
-
-
-typedef enum CvSubdiv2DPointLocation
-{
- CV_PTLOC_ERROR = -2,
- CV_PTLOC_OUTSIDE_RECT = -1,
- CV_PTLOC_INSIDE = 0,
- CV_PTLOC_VERTEX = 1,
- CV_PTLOC_ON_EDGE = 2
-}
-CvSubdiv2DPointLocation;
-
-typedef enum CvNextEdgeType
-{
- CV_NEXT_AROUND_ORG = 0x00,
- CV_NEXT_AROUND_DST = 0x22,
- CV_PREV_AROUND_ORG = 0x11,
- CV_PREV_AROUND_DST = 0x33,
- CV_NEXT_AROUND_LEFT = 0x13,
- CV_NEXT_AROUND_RIGHT = 0x31,
- CV_PREV_AROUND_LEFT = 0x20,
- CV_PREV_AROUND_RIGHT = 0x02
-}
-CvNextEdgeType;
-
-/* get the next edge with the same origin point (counterwise) */
-#define CV_SUBDIV2D_NEXT_EDGE( edge ) (((CvQuadEdge2D*)((edge) & ~3))->next[(edge)&3])
-
-
-/* Defines for Distance Transform */
-#define CV_DIST_USER -1 /* User defined distance */
-#define CV_DIST_L1 1 /* distance = |x1-x2| + |y1-y2| */
-#define CV_DIST_L2 2 /* the simple euclidean distance */
-#define CV_DIST_C 3 /* distance = max(|x1-x2|,|y1-y2|) */
-#define CV_DIST_L12 4 /* L1-L2 metric: distance = 2(sqrt(1+x*x/2) - 1)) */
-#define CV_DIST_FAIR 5 /* distance = c^2(|x|/c-log(1+|x|/c)), c = 1.3998 */
-#define CV_DIST_WELSCH 6 /* distance = c^2/2(1-exp(-(x/c)^2)), c = 2.9846 */
-#define CV_DIST_HUBER 7 /* distance = |x|<c ? x^2/2 : c(|x|-c/2), c=1.345 */
-
-
-/* Filters used in pyramid decomposition */
-typedef enum CvFilter
-{
- CV_GAUSSIAN_5x5 = 7
-}
-CvFilter;
-
-/****************************************************************************************/
-/* Older definitions */
-/****************************************************************************************/
-
-typedef float* CvVect32f;
-typedef float* CvMatr32f;
-typedef double* CvVect64d;
-typedef double* CvMatr64d;
-
-typedef struct CvMatrix3
-{
- float m[3][3];
-}
-CvMatrix3;
-
-
-#ifdef __cplusplus
-extern "C" {
-#endif
-
-typedef float (CV_CDECL * CvDistanceFunction)( const float* a, const float* b, void* user_param );
-
-#ifdef __cplusplus
-}
-#endif
-
-typedef struct CvConDensation
-{
- int MP;
- int DP;
- float* DynamMatr; /* Matrix of the linear Dynamics system */
- float* State; /* Vector of State */
- int SamplesNum; /* Number of the Samples */
- float** flSamples; /* arr of the Sample Vectors */
- float** flNewSamples; /* temporary array of the Sample Vectors */
- float* flConfidence; /* Confidence for each Sample */
- float* flCumulative; /* Cumulative confidence */
- float* Temp; /* Temporary vector */
- float* RandomSample; /* RandomVector to update sample set */
- struct CvRandState* RandS; /* Array of structures to generate random vectors */
-}
-CvConDensation;
-
-/*
-standard Kalman filter (in G. Welch' and G. Bishop's notation):
-
- x(k)=A*x(k-1)+B*u(k)+w(k) p(w)~N(0,Q)
- z(k)=H*x(k)+v(k), p(v)~N(0,R)
-*/
-typedef struct CvKalman
-{
- int MP; /* number of measurement vector dimensions */
- int DP; /* number of state vector dimensions */
- int CP; /* number of control vector dimensions */
-
- /* backward compatibility fields */
-#if 1
- float* PosterState; /* =state_pre->data.fl */
- float* PriorState; /* =state_post->data.fl */
- float* DynamMatr; /* =transition_matrix->data.fl */
- float* MeasurementMatr; /* =measurement_matrix->data.fl */
- float* MNCovariance; /* =measurement_noise_cov->data.fl */
- float* PNCovariance; /* =process_noise_cov->data.fl */
- float* KalmGainMatr; /* =gain->data.fl */
- float* PriorErrorCovariance;/* =error_cov_pre->data.fl */
- float* PosterErrorCovariance;/* =error_cov_post->data.fl */
- float* Temp1; /* temp1->data.fl */
- float* Temp2; /* temp2->data.fl */
-#endif
-
- CvMat* state_pre; /* predicted state (x'(k)):
- x(k)=A*x(k-1)+B*u(k) */
- CvMat* state_post; /* corrected state (x(k)):
- x(k)=x'(k)+K(k)*(z(k)-H*x'(k)) */
- CvMat* transition_matrix; /* state transition matrix (A) */
- CvMat* control_matrix; /* control matrix (B)
- (it is not used if there is no control)*/
- CvMat* measurement_matrix; /* measurement matrix (H) */
- CvMat* process_noise_cov; /* process noise covariance matrix (Q) */
- CvMat* measurement_noise_cov; /* measurement noise covariance matrix (R) */
- CvMat* error_cov_pre; /* priori error estimate covariance matrix (P'(k)):
- P'(k)=A*P(k-1)*At + Q)*/
- CvMat* gain; /* Kalman gain matrix (K(k)):
- K(k)=P'(k)*Ht*inv(H*P'(k)*Ht+R)*/
- CvMat* error_cov_post; /* posteriori error estimate covariance matrix (P(k)):
- P(k)=(I-K(k)*H)*P'(k) */
- CvMat* temp1; /* temporary matrices */
- CvMat* temp2;
- CvMat* temp3;
- CvMat* temp4;
- CvMat* temp5;
-}
-CvKalman;
-
-
-/*********************** Haar-like Object Detection structures **************************/
-#define CV_HAAR_MAGIC_VAL 0x42500000
-#define CV_TYPE_NAME_HAAR "opencv-haar-classifier"
-
-#define CV_IS_HAAR_CLASSIFIER( haar ) \
- ((haar) != NULL && \
- (((const CvHaarClassifierCascade*)(haar))->flags & CV_MAGIC_MASK)==CV_HAAR_MAGIC_VAL)
-
-#define CV_HAAR_FEATURE_MAX 3
-
-typedef struct CvHaarFeature
-{
- int tilted;
- struct
- {
- CvRect r;
- float weight;
- } rect[CV_HAAR_FEATURE_MAX];
-}
-CvHaarFeature;
-
-typedef struct CvHaarClassifier
-{
- int count;
- CvHaarFeature* haar_feature;
- float* threshold;
- int* left;
- int* right;
- float* alpha;
-}
-CvHaarClassifier;
-
-typedef struct CvHaarStageClassifier
-{
- int count;
- float threshold;
- CvHaarClassifier* classifier;
-
- int next;
- int child;
- int parent;
-}
-CvHaarStageClassifier;
-
-typedef struct CvHidHaarClassifierCascade CvHidHaarClassifierCascade;
-
-typedef struct CvHaarClassifierCascade
-{
- int flags;
- int count;
- CvSize orig_window_size;
- CvSize real_window_size;
- double scale;
- CvHaarStageClassifier* stage_classifier;
- CvHidHaarClassifierCascade* hid_cascade;
-}
-CvHaarClassifierCascade;
-
-typedef struct CvAvgComp
-{
- CvRect rect;
- int neighbors;
-}
-CvAvgComp;
-
-struct CvFeatureTree;
-
-#endif /*_CVTYPES_H_*/
-
-/* End of file. */
projects / opencv / blobdiff