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Delphi-OpenCV/include/imgproc/imgproc_c.pas
Laex 7b8c5d1a10 Many changes 
[*] Repository rebuilt
[*] CameraCalibrate - now working
[+] Improved cvSave
[+] Implemented macro CV_MAT_ELEM
[+] CvOpenFileStorage
and more ...

Signed-off-by: Laex <laex@bk.ru>
2013-04-02 02:17:25 +04:00

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unit imgproc_c;
{$ifdef DEBUG}
{$A8,B-,C+,D+,E-,F-,G+,H+,I+,J-,K-,L+,M-,N+,O-,P+,Q+,R+,S-,T-,U-,V+,W+,X+,Y+,Z1}
{$else}
{$A8,B-,C-,D-,E-,F-,G+,H+,I+,J-,K-,L-,M-,N+,O+,P+,Q-,R-,S-,T-,U-,V+,W-,X+,Y-,Z1}
{$endif}
{$WARN SYMBOL_DEPRECATED OFF}
{$WARN SYMBOL_PLATFORM OFF}
{$WARN UNIT_PLATFORM OFF}
{$WARN UNSAFE_TYPE OFF}
{$WARN UNSAFE_CODE OFF}
{$WARN UNSAFE_CAST OFF}
interface
(*
** 'C2PTypes.pas' declares external windows data types for the conversion purposes.
** It's created by the CtoPas converter and saved under
** "\Program Files\Common Files\AlGun Shared\CToPas 2.0\P_Files" folder.
** Consult the Windows and Delphi help files for more information about defined data types
*)
uses
Core.types_c, imgproc.types_c, types_c;
(* 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_IMGPROC_C_H__}
{$define __OPENCV_IMGPROC_IMGPROC_C_H__}
{$HPPEMIT '#include 'opencv2/core/core_c.h''}
{$HPPEMIT '#include 'opencv2/imgproc/types_c.h''}
{$ifdef __cplusplus}
//extern "C" {
{$endif}
(*********************** Background statistics accumulation **************************** *)
(* Adds image to accumulator *)
// CVAPI(procedure)cvAcc(var Adds squared image to accumulator * )
// CVAPI(procedure)cvSquareAcc(CvArr * image: v1: 0)): CvArr; (var sqsum: CvArr; var Adds a product of two images to accumulator * )
// CVAPI(procedure)cvMultiplyAcc(CvArr * image1: unction mask CV_DEFAULT(v1: 0)): CvArr; (;
// var image2: CvArr; var acc: CvArr; var Adds image to accumulator with weights: acc = acc * (1 - alpha) + image * alpha * )
// CVAPI(procedure)cvRunningAvg(CvArr * image: unction mask CV_DEFAULT(v1: 0)): CvArr; (;
// var acc: CvArr;alpha: Double;
// * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
// * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * \ * image Processing * * *
// * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
// * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * )
{
/* Copies source 2D array inside of the larger destination array and
makes a border of the specified type (IPL_BORDER_*) around the copied area. */
CVAPI(void) cvCopyMakeBorder(
const CvArr* src,
CvArr* dst,
CvPoint offset,
int bordertype,
CvScalar value CV_DEFAULT(cvScalarAll(0)));
}
procedure cvCopyMakeBorder(
{ } const src: pIplImage;
{ } dst: pIplImage;
{ } offset: TCvPoint;
{ } bordertype: Integer;
{ } value: TCvScalar { * cvScalarAll(0) * } ); cdecl;
// Smoothes array (removes noise) * )
// CVAPI(
// procedure)cvSmooth(CvArr * src: CvScalar value CV_DEFAULT(v1: 0))): Integer; (; var dst: CvArr;
// smoothtype CV_DEFAULT(v1: 3:
// function); size2 CV_DEFAULT(0): Integer; sigma1 CV_DEFAULT(0):
// function; sigma2 CV_DEFAULT(0): Double): Integer;
{
// Smoothes array (removes noise)
CVAPI(void) cvSmooth(
const CvArr* src,
CvArr* dst,
int smoothtype CV_DEFAULT(CV_GAUSSIAN),
int size1 CV_DEFAULT(3),
int size2 CV_DEFAULT(0),
double sigma1 CV_DEFAULT(0),
double sigma2 CV_DEFAULT(0));
}
procedure cvSmooth(
{ } const src: pIplImage;
{ } dst: pIplImage;
{ } smoothtype: Integer = CV_GAUSSIAN;
{ } size1: Integer = 3;
{ } size2: Integer = 0;
{ } sigma1: double = 0;
{ } sigma2: double = 0); cdecl;
// (* Convolves the image with the kernel *)
// CVAPI(
// procedure)cvFilter2D(v1: CvPoint(-1;
//
{
Finds integral image: SUM(X,Y) = sum(x<X,y<Y)I(x,y)
CVAPI(void) cvIntegral(
const CvArr* image,
CvArr* sum,
CvArr* sqsum CV_DEFAULT(NULL),
CvArr* tilted_sum CV_DEFAULT(NULL));
}
procedure cvIntegral(
{ } const image: pIplImage;
{ } sum: pIplImage;
{ } sqsum: pIplImage = NIL;
{ } tilted_sum: pIplImage = NIL); cdecl;
// var
// Finds integral image: SUM(X: 1))): Double; (; = SUM(X < X: ); v4: < Y)I(X;
// var)CVAPI(procedure)cvIntegral(CvArr * image: ); var SUM: CvArr;
// Smoothes the input image with gaussian kernel and then down - samples it.dst_width = floor
// (src_width / 2): array [0 .. 0] of var function sqsum CV_DEFAULT(v1: 0)): CvArr; (;
// * src dst_height = floor(src_height / 2): array [0 .. 0] of var)CVAPI(procedure)cvPyrDown(CvArr;
// var dst: CvArr; var Up - samples image and Smoothes the cResult with gaussian kernel.dst_width =
// src_width * 2: function filter CV_DEFAULT(v1: CV_GAUSSIAN_5x5)): Integer; (;
// var 2 * )CVAPI(procedure)cvPyrUp(CvArr * src: dst_height = src_height; var dst: CvArr;
// var Builds pyramid for an image * )CVAPI(CvMat * )cvCreatePyramid(const CvArr * img
// : function filter CV_DEFAULT(v1: CV_GAUSSIAN_5x5)): Integer; (; extra_layers: int; rate: Double;
// var layer_sizes CV_DEFAULT(0): vSize; bufarr CV_DEFAULT(v1: 1: function);
// filter CV_DEFAULT(CV_GAUSSIAN_5x5): Integer): Integer;
//
// (* Releases pyramid *)
// CVAPI(procedure)cvReleasePyramid(v1: var Filters image using meanshift algorithm * )
// CVAPI(procedure)cvPyrMeanShiftFiltering(CvArr * src; var dst: CvArr; sp: function; sr: Double;
// var Segments image using seed " markers " * )CVAPI(procedure)cvWatershed(CvArr * image
// : function max_level CV_DEFAULT(v1: cvTermCriteria(CV_TERMCRIT_ITER + CV_TERMCRIT_EPS;
// :;
// v3: ))): Integer; (; var markers): Double;
// (* Calculates an image derivative using generalized Sobel (aperture_size = 1: CvArr;
// : ;
// : ;
// var )
{
/* Calculates an image derivative using generalized Sobel
(aperture_size = 1,3,5,7) or Scharr (aperture_size = -1) operator.
Scharr can be used only for the first dx or dy derivative */
CVAPI(void) cvSobel(
const CvArr* src,
CvArr* dst,
int xorder,
int yorder,
int aperture_size CV_DEFAULT(3));
}
procedure cvSobel(const src: pIplImage; dst: pIplImage; xorder: Integer; yorder: Integer;
aperture_size: Integer = 3); cdecl;
{
/* Calculates the image Laplacian: (d2/dx + d2/dy)I */
CVAPI(void) cvLaplace(
const CvArr* src,
CvArr* dst,
int aperture_size CV_DEFAULT(3) );
}
procedure cvLaplace(const src: pIplImage; dst: pIplImage; aperture_size: Integer = 3); cdecl;
(* Converts input array pixels from one color space to another *)
// CVAPI(void) cvCvtColor( const CvArr* src, CvArr* dst, int code );
procedure cvCvtColor(const src: pIplImage; dst: pIplImage; code: Integer); cdecl;
//
// (* Resizes image (input array is resized to fit the destination array) *)
// CVAPI(procedure)cvResize(var Warps image with affine transform * )
{
CVAPI(void) cvResize( const CvArr* src, CvArr* dst,
int interpolation CV_DEFAULT( CV_INTER_LINEAR ));
}
procedure cvResize(const src: TCvArr; dst: TCvArr; interpolation: Integer = CV_INTER_LINEAR); cdecl;
// CVAPI(procedure)cvWarpAffine(CvArr
// * src: ): CV_INTER_LINEAR): Integer; (; var dst: CvArr; var map_matrix: CvMat;
// Computes affine transform matrix for mapping src: array [0 .. I - 1] of var to dst[I]
// (I = 0 function flags CV_DEFAULT(v1: cvScalarAll(
// 0))): Integer; (; :; var)
// CVAPI(CvMat)cvGetAffineTransform(CvPoint2D32f * src: );
// var dst: vPoint2D32f; var map_matrix: CvMat);
//
// (* Computes rotation_matrix matrix *)
// CVAPI(CvMat)cv2DRotationMatrix(CvPoint2D32f center, Double angle, Double scale, CvMat * map_matrix);
//
// (* Warps image with perspective (projective) transform *)
// CVAPI(
// procedure)cvWarpPerspective(Computes perspective transform matrix for mapping src: array [0 .. I -
// 1] of var to dst[I](I = 0 v1: cvScalarAll(0))): Integer; (; :; :;
// var)CVAPI(CvMat)cvGetPerspectiveTransform(CvPoint2D32f * src: ); var dst: vPoint2D32f;
// var map_matrix: CvMat);
//
{
/* Performs generic geometric transformation using the specified coordinate maps */
CVAPI(void) cvRemap(
const CvArr* src,
CvArr* dst,
const CvArr* mapx,
const CvArr* mapy,
int flags CV_DEFAULT(CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS),
CvScalar fillval CV_DEFAULT(cvScalarAll(0)) );
}
procedure cvRemap(const src: pIplImage; dst: pIplImage; const mapx: pIplImage; const mapy: pIplImage;
flags: Integer { =CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS }; fillval: TCvScalar { =cvScalarAll(0) }
); cdecl;
// (* Performs forward or inverse log-polar image transform *)
// CVAPI(
// procedure)cvLogPolar(var Performs forward or inverse linear - polar image transform * )CVAPI(
// procedure)cvLinearPolar(CvArr * src: v1: CV_INTER_LINEAR + CV_WARP_FILL_OUTLIERS)): Integer; (;
// var dst: CvArr; center: CvPoint2D32f; maxRadius: Double;
// var Transforms the input image to compensate lens distortion * )CVAPI(
// procedure)cvUndistort2(CvArr * src:
// function flags CV_DEFAULT(v1: CV_INTER_LINEAR + CV_WARP_FILL_OUTLIERS)): Integer; (; var dst: CvArr;
// var camera_matrix: vMat; var distortion_coeffs: vMat; var new_camera_matrix CV_DEFAULT(0): vMat);
//
{
/* Computes transformation map from intrinsic camera parameters
that can used by cvRemap */
CVAPI(void) cvInitUndistortMap(
const CvMat* camera_matrix,
const CvMat* distortion_coeffs,
CvArr* mapx,
CvArr* mapy );
}
procedure cvInitUndistortMap(const camera_matrix: pCvMat; const distortion_coeffs: pCvMat; mapx: pIplImage;
mapy: pIplImage); cdecl;
// (* Computes undistortion+rectification map for a head of stereo camera *)
// CVAPI(
// procedure)cvInitUndistortRectifyMap(var camera_matrix: CvMat; var dist_coeffs: vMat;
// var = new_camera_matrix: onst CvMat; var } CvArr * mapx: {$EXTERNALSYM CvMat;
// var mapy: CvArr);
//
// (* Computes the original (undistorted) feature coordinates
// from the observed (distorted) coordinates *)
// CVAPI(procedure) cvUndistortPoints(
// v1: 0);
// var P CV_DEFAULT(0): vMat);
//
// (* creates structuring element used for morphological operations *)
// CVAPI(IplConvKernel) cvCreateStructuringElementEx(
// Integer cols, Integer rows, Integer anchor_x, Integer anchor_y,
// function shape, Integer values CV_DEFAULT(v1: 0)): Integer;
// CVAPI(IplConvKernel*) cvCreateStructuringElementEx(
// int cols, int rows, int anchor_x, int anchor_y,
// int shape, int* values CV_DEFAULT(NULL) );
function cvCreateStructuringElementEx(cols: Integer; rows: Integer; anchor_x: Integer; anchor_y: Integer;
shape: Integer; values: pInteger = nil): pIplConvKernel; cdecl;
// (* releases structuring element *)
// CVAPI(procedure) cvReleaseStructuringElement( element: array of IplConvKernel);
// CVAPI(void) cvReleaseStructuringElement( IplConvKernel** element );
procedure cvReleaseStructuringElement(Var element: pIplConvKernel); cdecl;
//
// (* erodes input image (applies minimum filter) one or more times.
// If element cPointer is 0, 3x3 rectangular element is used *)
// CVAPI(procedure) cvErode(
// v1: 0);
// var dilates input image (applies maximum filter) one or more times. If element cPointer is 0: function iterations CV_DEFAULT(v1: 1)): Integer;(;
// var )
// CVAPI(procedure) cvDilate( CvArr* src: 3x3 rectangular element is used;
// var dst: CvArr;
// var element CV_DEFAULT(0): IplConvKernel;
// var Performs complex morphological transformation *)
// CVAPI(procedure) cvMorphologyEx( CvArr* src: function iterations CV_DEFAULT(v1: 1)): Integer;(;
// var dst: CvArr;
// var temp: CvArr;
// var element: IplConvKernel;
// operation: function;
// var Calculates all spatial and central moments up to the 3rd order *)
{ Performs complex morphological transformation }
// CVAPI(void) cvMorphologyEx( const CvArr* src, CvArr* dst,
// CvArr* temp, IplConvKernel* element,
// int operation, int iterations CV_DEFAULT(1) );
procedure cvMorphologyEx(const src: pIplImage; dst: pIplImage; temp: pIplImage; element: pIplConvKernel;
operation: Integer; iterations: Integer = 1); cdecl;
// CVAPI(procedure) cvMoments( CvArr* arr: Integer iterations CV_DEFAULT(v1: 1)): Integer;(;
// var moments: CvMoments;
// binary CV_DEFAULT(0): Integer);
{ erodes input image (applies minimum filter) one or more times.
If element pointer is NULL, 3x3 rectangular element is used }
// CVAPI(void) cvErode( const CvArr* src, CvArr* dst,
// IplConvKernel* element CV_DEFAULT(NULL),
// int iterations CV_DEFAULT(1) );
procedure cvErode(const src: pIplImage; dst: pIplImage; element: pIplConvKernel = nil; iterations: Integer = 1); cdecl;
{ dilates input image (applies maximum filter) one or more times.
If element pointer is NULL, 3x3 rectangular element is used }
// CVAPI(void) cvDilate( const CvArr* src, CvArr* dst,
// IplConvKernel* element CV_DEFAULT(NULL),
// int iterations CV_DEFAULT(1) );
procedure cvDilate(const src: pIplImage; dst: pIplImage; element: pIplConvKernel = nil; iterations: Integer = 1); cdecl;
//
// (* Retrieve particular spatial, central or normalized central moments *)
// CVAPI(Double) cvGetSpatialMoment( CvMoments* moments, Integer x_order, Integer y_order );
// CVAPI(Double) cvGetCentralMoment( CvMoments* moments, Integer x_order, Integer y_order );
// CVAPI(Double) cvGetNormalizedCentralMoment( CvMoments* moments,
// Integer x_order, Integer y_order );
//
// (* Calculates 7 Hu's invariants from precalculated spatial and central moments */
// CVAPI(procedure) cvGetHuMoments(var moments: CvMoments; var hu_moments: CvHuMoments);
//
// (*********************************** data sampling **************************************)
//
// (* Fetches pixels that belong to the specified line segment and stores them to the buffer.
// Returns the number of retrieved points. *)
// CVAPI(Integer) cvSampleLine( CvArr* image, CvPoint pt1, CvPoint pt2, Pointer buffer,
// function connectivity CV_DEFAULT(v1: 8)): Integer;
//
// (* Retrieves the rectangular image region with specified center from the input array.
// dst(x,y) <- src(x + center.x - dst_width/2, y + center.y - dst_height/2).
// Values of pixels with fractional coordinates are retrieved using bilinear interpolation*)
// CVAPI(procedure) cvGetRectSubPix(var src: CvArr; var dst: CvArr; center: CvPoint2D32f);
//
//
// (* Retrieves quadrangle from the input array.
// = ( a11 a12 or b1 ) dst(x,y) <- src(A : array[0..x y-1] of matrixarr' + b)
// ( a21 a22 or b2 ) (bilinear interpolation is used to retrieve pixels
// with fractional coordinates)
// *)
// CVAPI(procedure) cvGetQuadrangleSubPix(
// var src: CvArr;
// var dst: CvArr;
// var map_matrix: vMat);
//
// (* Measures similarity between template and overlapped windows in the source image
// and fills the resultant image with the measurements *)
// CVAPI(procedure) cvMatchTemplate(
// var image: CvArr;
// var templ: CvArr;
// var cResult: CvArr;
// method: Integer);
//
// (* Computes earth mover distance between
// two weighted point sets (called signatures) *)
// CVAPI(Single) cvCalcEMD2( CvArr* signature1,
// CvArr* signature2,
// Integer distance_type,
// CvDistanceFunction distance_func CV_DEFAULT(0),
// function cost_matrix CV_DEFAULT(
// v1: 0);
// lower_bound CV_DEFAULT(0): function;
// userdata CV_DEFAULT(0): function): Single;
//
// (****************************************************************************************\
// * Contours retrieving *
// ****************************************************************************************)
Type
PCvContour = ^TCvContour;
TCvContour = packed record
flags: Integer; // * micsellaneous flags */ \
header_size: Integer; // * size of sequence header */ \
h_prev: PCvSeq; // * previous sequence */ \
h_next: PCvSeq; // * next sequence */ \
v_prev: PCvSeq; // * 2nd previous sequence */ \
v_next: PCvSeq; // * 2nd next sequence */
total: Integer; // * total number of elements */ \
elem_size: Integer; // * size of sequence element in bytes */ \
block_max: PAnsiChar; // * maximal bound of the last block */ \
ptr: PAnsiChar; // * current write pointer */ \
delta_elems: Integer; // * how many elements allocated when the seq grows */ \
storage: PCvMemStorage; // * where the seq is stored */ \
free_blocks: PCvSeqBlock; // * free blocks list */ \
first: PCvSeqBlock; // * pointer to the first sequence block */
rect: TCvRect;
color: Integer;
reserved: array [0 .. 2] of Integer;
end;
Const
// * contour retrieval mode */
CV_RETR_EXTERNAL = 0;
CV_RETR_LIST = 1;
CV_RETR_CCOMP = 2;
CV_RETR_TREE = 3;
// * contour approximation method */
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;
{
/* Retrieves outer and optionally inner boundaries of white (non-zero) connected
components in the black (zero) background */
CVAPI(int) cvFindContours(
CvArr* image,
CvMemStorage* storage,
CvSeq** first_contour,
int header_size CV_DEFAULT(sizeof(CvContour)),
int mode CV_DEFAULT(CV_RETR_LIST),
int method CV_DEFAULT(CV_CHAIN_APPROX_SIMPLE),
CvPoint offset CV_DEFAULT(cvPoint(0,0)));
}
function cvFindContours(
{ } image: pIplImage;
{ } storage: PCvMemStorage;
{ } first_contour: PCvSeq;
{ } header_size: Integer { = SizeOf(TCvContour) };
{ } mode: Integer { = CV_RETR_LIST };
{ } method: Integer { = CV_CHAIN_APPROX_SIMPLE };
{ } offset: TCvPoint { =cvPoint(0,0) } ): Integer; cdecl;
//
// (* Initalizes contour retrieving process.
// Calls cvStartFindContours.
// Calls cvFindNextContour until null cPointer is returned
// or some other condition becomes true.
// Calls cvEndFindContours at the end. *)
// CVAPI(CvContourScanner) cvStartFindContours( CvArr* image, CvMemStorage* storage,
// function header_size CV_DEFAULT(
// v1: CvContour));
// mode CV_DEFAULT(CV_RETR_LIST): Integer;
// method CV_DEFAULT(CV_CHAIN_APPROX_SIMPLE): Integer;
// offset CV_DEFAULT(cvPoint(0: CvPoint;
// v5: ))): Integer;
//
// (* Retrieves next contour *)
// CVAPI(CvSeq) cvFindNextContour( CvContourScanner scanner ): Pointer;
//
//
// (* Substitutes the last retrieved contour with the new one
// (if the substitutor is null, the last retrieved contour is removed from the tree) *) then
// CVAPI(procedure) cvSubstituteContour(
// v1: var Releases contour scanner and returns pointer to the first outer contour *)CVAPI(CvSeq) cvEndFindContours( CvContourScanner* scanner);
//
// (* Approximates a single Freeman chain or a tree of chains to polygonal curves *)
// CVAPI(CvSeq) cvApproxChains( CvSeq* src_seq, CvMemStorage* storage,
// function method CV_DEFAULT(
// v1: 0);
// minimal_perimeter CV_DEFAULT(0): Integer;
// recursive CV_DEFAULT(0): Integer): Integer;
//
// (* Initalizes Freeman chain reader.
// The reader is used to iteratively get coordinates of all the chain points.
// If the Freeman codes should be read as is, a simple sequence reader should be used *)
// CVAPI(procedure) cvStartReadChainPoints(
// v1: var Retrieves the next chain point *)CVAPI(CvPoint) cvReadChainPoint( CvChainPtReader* reader);
//
//
// (****************************************************************************************\
// * Contour Processing and Shape Analysis *
// ****************************************************************************************)
{
/* Approximates a single polygonal curve (contour) or
a tree of polygonal curves (contours) */
CVAPI(CvSeq*) cvApproxPoly(
const void* src_seq,
int header_size,
CvMemStorage* storage,
int method,
double eps,
int recursive CV_DEFAULT(0));
}
function cvApproxPoly(
{ } const src_seq: PCvSeq;
{ } header_size: Integer;
{ } storage: PCvMemStorage;
{ } method: Integer;
{ } eps: double;
{ } recursive: Integer = 0): PCvSeq; cdecl;
//
// (* Calculates perimeter of a contour or length of a part of contour *)
// CVAPI(Double) cvArcLength( Pointer curve,
// CvSlice slice CV_DEFAULT(CV_WHOLE_SEQ),
// function is_closed CV_DEFAULT(v1: -1)): Integer;
//
// CV_INLINE function cvContourPerimeter(v1: contour; v2: CV_WHOLE_SEQ; : ): Double;
// end;
//
//
// (* Calculates contour boundning rectangle (update=1) or
// just retrieves pre-calculated rectangle (update=0) *)
// CVAPI(CvRect) cvBoundingRect( CvArr* points, Integer update CV_DEFAULT(0) );
//
// (* Calculates area of a contour or contour segment *)
// CVAPI(Double) cvContourArea( CvArr* contour,
// CvSlice slice CV_DEFAULT(CV_WHOLE_SEQ),
// function oriented CV_DEFAULT(v1: 0)): Integer;
//
// (* Finds minimum area rotated rectangle bounding a set of points *)
// CVAPI(CvBox2D) cvMinAreaRect2( CvArr* points,
// CvMemStorage* storage CV_DEFAULT(0));
//
// (* Finds minimum enclosing circle for a set of points *)
// CVAPI(Integer) cvMinEnclosingCircle( CvArr* points,
// CvPoint2D32f* center, Single* radius );
//
// (* Compares two contours by matching their moments *)
// CVAPI(Double) cvMatchShapes( Pointer object1, Pointer object2,
// function method, function parameter CV_DEFAULT(v1: 0)): Integer;
//
// (* Calculates exact convex hull of 2d point set *)
// CVAPI(CvSeq) cvConvexHull2( CvArr* input,
// function hull_storage CV_DEFAULT(
// v1: CV_CLOCKWISE);
// return_points CV_DEFAULT(0): Integer): Integer;
//
// (* Checks whether the contour is convex or not (returns 1 if convex, 0 if not) *)
// CVAPI(Integer) cvCheckContourConvexity( CvArr* contour ): Double;
//
//
// (* Finds convexity defects for the contour *)
// CVAPI(CvSeq) cvConvexityDefects( CvArr* contour, CvArr* convexhull,
// CvMemStorage* storage CV_DEFAULT(0)): Pointer;
//
// (* Fits ellipse into a set of 2d points *)
// CVAPI(CvBox2D) cvFitEllipse2( CvArr* points );
//
// (* Finds minimum rectangle containing two given rectangles *)
// CVAPI(CvRect) cvMaxRect( CvRect* rect1, CvRect* rect2 );
//
// (* Finds coordinates of the box vertices *)
// cvBoxPoints(box CvBox2D; pt : array[0..3] of CVAPI(procedure): CvPoint2D32f);
//
// (* Initializes sequence header for a matrix (column or row vector) of points -
// a wrapper for cvMakeSeqHeaderForArray (it does not initialize bounding rectangle not not not ) *)
// CVAPI(CvSeq) cvPointSeqFromMat( Integer seq_kind, CvArr* mat,
// CvContour* contour_header,
// CvSeqBlock* block );
//
// (* Checks whether the point is inside polygon, outside, on an edge (at a vertex).
// Returns positive, negative or zero value, correspondingly.
// Optionally, measures a Integer distance between
// the point and the nearest polygon edge (measure_dist=1) *)
// CVAPI(Double) cvPointPolygonTest( CvArr* contour,
// CvPoint2D32f pt, Integer measure_dist );
//
// (****************************************************************************************\
// * Histogram functions *
// ****************************************************************************************)
//
// (* Creates new histogram *)
// CVAPI(CvHistogram) cvCreateHist( Integer dims, Integer* sizes, Integer cType,
// function * ranges CV_DEFAULT(v1: 1)): Integer;
//
// (* Assignes histogram bin ranges *)
// CVAPI(procedure) cvSetHistBinRanges(
// var Creates histogram header for array *)CVAPI(CvHistogram) cvMakeHistHeaderForArray( Integer dims: v1: 1)): Integer;(;
// var sizes: Integer;
// var hist: CvHistogram;
// var function: Single;
// var ranges CV_DEFAULT(v1: 1)): Integer;(* Releases histogram *)CVAPI(procedure) cvReleaseHist( CvHistogram** hist ): Single;(* Clears all the histogram bins *)CVAPI(procedure) cvClearHist( CvHistogram* hist ): data;(* Finds indices and values of minimum and maximum histogram bins *)CVAPI(procedure) cvGetMinMaxHistValue( CvHistogram* hist: Single;
// var min_value: Single;
// var max_value: Single;
// var Normalizes histogram by dividing all bins by sum of the bins: function min_idx CV_DEFAULT(v1: 0)): Integer;(;
// var )CVAPI(procedure) cvNormalizeHist( CvHistogram* hist: multiplied by <factor>. After that sum of histogram bins is equal to <factor>;
// factor: Double);
//
//
// (* Clear all histogram bins that are below the threshold *)
// CVAPI(procedure) cvThreshHist(var hist: CvHistogram; threshold: Double);
//
//
// (* Compares two histogram *)
// CVAPI(Double) cvCompareHist( CvHistogram* hist1,
// CvHistogram* hist2,
// Integer method);
//
// (* Copies one histogram to another. Destination histogram is created if
// the destination cPointer is 0 *)
// CVAPI(procedure) cvCopyHist(var src: CvHistogram; dst: array of CvHistogram);
//
//
// (* Calculates bayesian probabilistic histograms
// (each or src and dst is an cArray of <number> histograms *)
// CVAPI(procedure) cvCalcBayesianProb(
// src: array of CvHistogram;
// number: Integer;
// dst: array of CvHistogram);
//
// (* Calculates array histogram *)
// CVAPI(procedure) cvCalcArrHist(
// image: array of v1: 0)): Integer;CV_INLINE CV_INLINE procedure cvCalcHist( IplImage;
// var hist: CvHistogram;
// accumulate CV_DEFAULT(0): Integer;
// var mask CV_DEFAULT(0) )begin cvCalcArrHist( (CvArr*)image: vArr;
// v5: hist;
// v6: accumulate;
// var Calculates back project *)CVAPI(procedure) cvCalcArrBackProject( CvArr** image: mask ): CvArr; end;(;
// var dst: CvArr;
// var hist: vHistogram);
/// / >> Following declaration is a macro definition!
// const cvCalcBackProject(image, dst, hist) cvCalcArrBackProject((CvArr;
//
//
// (* Does some sort of template matching but compares histograms of
// template and each window location *)
// CVAPI(procedure) cvCalcArrBackProjectPatch(
// image: array of CvArr;
// var dst: CvArr;
// range: CvSize;
// var hist: CvHistogram;
// method: Integer;
// factor: Double);
/// / >> Following declaration is a macro definition!
// const cvCalcBackProjectPatch( image, dst, range, hist, method, factor ) cvCalcArrBackProjectPatch( (CvArr;
//
// (* calculates probabilistic density (divides one histogram by another) *)
// CVAPI(procedure) cvCalcProbDensity(
{ /* equalizes histogram of 8-bit single-channel image */
CVAPI(void) cvEqualizeHist( const CvArr* src, CvArr* dst );
}
procedure cvEqualizeHist(const src, dst: pIplImage); cdecl;
//
//
// (* Applies distance transform to binary image *)
// CVAPI(procedure) cvDistTransform(
// 3: v1:);
// mask CV_DEFAULT(0): unction;
// labels CV_DEFAULT(0): function;
// labelType CV_DEFAULT(CV_DIST_LABEL_CCOMP): Integer): Integer;
//
//
// (* Applies fixed-level threshold to grayscale image.
// This is a basic operation applied before retrieving contours *)
// CVAPI(double) cvThreshold( const CvArr* src, CvArr* dst, double threshold, double max_value, int threshold_type );
function cvThreshold(const src, dst: pIplImage; threshold, max_value: double; threshold_type: Integer): double; cdecl;
{
/* Applies adaptive threshold to grayscale image.
The two parameters for methods CV_ADAPTIVE_THRESH_MEAN_C and
CV_ADAPTIVE_THRESH_GAUSSIAN_C are:
neighborhood size (3, 5, 7 etc.),
and a constant subtracted from mean (...,-3,-2,-1,0,1,2,3,...) */
CVAPI(void) cvAdaptiveThreshold(
const CvArr* src,
CvArr* dst,
double max_value,
int adaptive_method CV_DEFAULT(CV_ADAPTIVE_THRESH_MEAN_C),
int threshold_type CV_DEFAULT(CV_THRESH_BINARY),
int block_size CV_DEFAULT(3),
double param1 CV_DEFAULT(5));
}
procedure cvAdaptiveThreshold(
{ } const src: pIplImage;
{ } dst: pIplImage;
{ } max_value: double;
{ } adaptive_method: Integer = CV_ADAPTIVE_THRESH_MEAN_C;
{ } threshold_type: Integer = CV_THRESH_BINARY;
{ } block_size: Integer = 3;
{ } param1: double = 5); cdecl;
{
/* Fills the connected component until the color difference gets large enough */
CVAPI(void) cvFloodFill(
CvArr* image,
CvPoint seed_point,
CvScalar new_val,
CvScalar lo_diff CV_DEFAULT(cvScalarAll(0)),
CvScalar up_diff CV_DEFAULT(cvScalarAll(0)),
CvConnectedComp* comp CV_DEFAULT(NULL),
int flags CV_DEFAULT(4),
CvArr* mask CV_DEFAULT(NULL));
}
procedure cvFloodFill(
{ } image: pIplImage;
{ } seed_point: TCvPoint;
{ } new_val: TCvScalar;
{ } lo_diff: TCvScalar { * cvScalarAll(0) * };
{ } up_diff: TCvScalar { * cvScalarAll(0) * };
{ } comp: pCvConnectedComp = NIL;
{ } flags: Integer = 4;
{ } mask: PCvArr = NIL); cdecl;
// ****************************************************************************************
// * Feature detection *
// ****************************************************************************************
{
/* Runs canny edge detector */
CVAPI(void) cvCanny(
const CvArr* image,
CvArr* edges,
double threshold1,
double threshold2,
int aperture_size CV_DEFAULT(3) );
}
procedure cvCanny(const image: pIplImage; edges: pIplImage; threshold1: double; threshold2: double;
aperture_size: Integer = 3); cdecl;
// (* Runs canny edge detector *) CVAPI(
// procedure)cvCanny(CvArr * image: array of
// function flags CV_DEFAULT(v1: 0)): Integer; (; var edges: CvArr; threshold1: Double;
// threshold2: Double; var Calculates constraint image for corner detection Dx xor 2 * Dyy + Dxx *
// Dy xor 2 - 2 * Dx * Dy * Dxy.Applying threshold to the cResult gives coordinates of
// corners * )
// CVAPI(
// procedure)cvPreCornerDetect(CvArr * image:
// function aperture_size CV_DEFAULT(v1: 3)): Integer; (; var corners: CvArr;
// var Calculates eigen values and vectors of 2 x2 gradient covariation matrix at every image
// pixel * )CVAPI(
// procedure)cvCornerEigenValsAndVecs(CvArr * image:
// function aperture_size CV_DEFAULT(v1: 3)): Integer; (; var eigenvv: CvArr; block_size:
// function; var Calculates minimal eigenvalue for 2 x2 gradient covariation matrix at every image
// pixel * )CVAPI(
// procedure)cvCornerMinEigenVal(CvArr * image: Integer aperture_size CV_DEFAULT(v1: 3)): Integer; (;
// var eigenval: CvArr; block_size:
// function; var Harris corner detector: Calculates det(M) - k * (trace(M) xor 2)
// : Integer aperture_size CV_DEFAULT(v1: 3)): Integer; (; var)CVAPI(
// procedure)cvCornerHarris(CvArr * image: where M is 2 x2 gradient covariation matrix for each pixel;
// var harris_responce: CvArr; block_size:
{
/* Adjust corner position using some sort of gradient search */
CVAPI(void) cvFindCornerSubPix(
const CvArr* image,
CvPoint2D32f* corners,
int count,
CvSize win,
CvSize zero_zone,
CvTermCriteria criteria );
}
procedure cvFindCornerSubPix(const image: pIplImage; corners: pCvPoint2D32f; count: Integer; win: TCvSize;
zero_zone: TCvSize; criteria: TCvTermCriteria); cdecl;
// function; var Adjust corner position using some sort of gradient search * )CVAPI(
// procedure)cvFindCornerSubPix(CvArr * image: Integer aperture_size CV_DEFAULT(v1: 0.04)): Integer; (;
// var corners: CvPoint2D32f; count: Integer; win: CvSize; zero_zone: CvSize;
// var Finds a sparse set of points within the selected region that seem to be easy to track * )CVAPI(
// procedure)cvGoodFeaturesToTrack(CvArr * image: cvTermCriteria criteria): Double; (;
// var eig_image: CvArr; var temp_image: CvArr; var corners: CvPoint2D32f; var corner_count: Integer;
// quality_level: Double; min_distance: Double; var mask CV_DEFAULT(0): vArr;
// block_size CV_DEFAULT(v1: 0:
// function); k CV_DEFAULT(0.04):
// function): Integer;
//
// (* Finds lines on binary image using one of several methods.
// line_storage is either memory storage or 1 x <max number of lines> CvMat, its
// number of columns is changed by the cFunction.
// method is one of CV_HOUGH_*;
// rho, theta and threshold are used for each of those methods;
// param1 ~ line length, param2 ~ line gap - for probabilistic,
// param1 ~ srn, param2 ~ stn - for multi-scale *)
// CVAPI(CvSeq)cvHoughLines2(CvArr * image, Pointer line_storage, Integer method, Double rho,
// Double theta, Integer threshold, Double param1 CV_DEFAULT(0), Double param2 CV_DEFAULT(0)
// ): Double;
{
/* Finds lines on binary image using one of several methods.
line_storage is either memory storage or 1 x <max number of lines> CvMat, its
number of columns is changed by the function.
method is one of CV_HOUGH_*;
rho, theta and threshold are used for each of those methods;
param1 ~ line length, param2 ~ line gap - for probabilistic,
param1 ~ srn, param2 ~ stn - for multi-scale */
CVAPI(CvSeq*) cvHoughLines2(
CvArr* image,
void* line_storage,
int method,
double rho,
double theta,
int threshold,
double param1 CV_DEFAULT(0),
double param2 CV_DEFAULT(0));
}
function cvHoughLines2(
{ } image: pIplImage;
{ } line_storage: Pointer;
{ } method: Integer;
{ } rho: double;
{ } theta: double;
{ } threshold: Integer;
{ } param1: double = 0;
{ } param2: double = 0): PCvSeq; cdecl;
{
/* Finds circles in the image */
CVAPI(CvSeq*) cvHoughCircles(
CvArr* image,
void* circle_storage,
int method,
double dp,
double min_dist,
double param1 CV_DEFAULT(100),
double param2 CV_DEFAULT(100),
int min_radius CV_DEFAULT(0),
int max_radius CV_DEFAULT(0));
}
function cvHoughCircles(
{ } image: pIplImage;
{ } circle_storage: Pointer;
{ } method: Integer;
{ } dp: double;
{ } min_dist: double;
{ } param1: double = 100;
{ } param2: double = 100;
{ } min_radius: Integer = 0;
{ } max_radius: Integer = 0): PCvSeq; cdecl;
// (* Fits a line into set of 2d or 3d points in a robust way (M-estimator technique) *)
// CVAPI(
// procedure)cvFitLine(CvArr * points, Integer dist_type, Double param, Double reps, Double aeps,
// Single * line): Double;
//
// {$IFDEF __cplusplus}
// end;
// {$ENDIF}
// {$ENDIF}
implementation
Uses uLibName;
procedure cvCvtColor; external imgproc_Dll;
function cvThreshold; external imgproc_Dll;
procedure cvSmooth; external imgproc_Dll;
procedure cvResize; external imgproc_Dll;
function cvCreateStructuringElementEx; external imgproc_Dll;
procedure cvErode; external imgproc_Dll;
procedure cvDilate; external imgproc_Dll;
procedure cvReleaseStructuringElement; external imgproc_Dll;
procedure cvMorphologyEx; external imgproc_Dll;
procedure cvFloodFill; external imgproc_Dll;
procedure cvAdaptiveThreshold; external imgproc_Dll;
procedure cvCopyMakeBorder; external imgproc_Dll;
procedure cvSobel; external imgproc_Dll;
procedure cvLaplace; external imgproc_Dll;
procedure cvCanny; external imgproc_Dll;
function cvHoughLines2; external imgproc_Dll;
function cvHoughCircles; external imgproc_Dll;
procedure cvIntegral; external imgproc_Dll;
function cvFindContours; external imgproc_Dll;
function cvApproxPoly; external imgproc_Dll;
procedure cvEqualizeHist; external imgproc_Dll;
procedure cvFindCornerSubPix; external imgproc_Dll;
procedure cvInitUndistortMap; external imgproc_Dll;
procedure cvRemap; external imgproc_Dll;
end.
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