《zw版·Halcon-delphi系列原创教程》 Halcon分类函数007, match，图像匹配

《zw版·Halcon-delphi系列原创教程》 Halcon分类函数007, match，图像匹配

为方便阅读，在不影响说明的前提下，笔者对函数进行了简化：

• :: 用符号“**”，替换：“procedure”
• :: 用大写字母“X”，替换：“IHUntypedObjectX”
• :: 省略了字符：“const”、“OleVariant”

【示例】 说明

函数：

procedure AddNoiseWhiteContourXld( const Contours: IHUntypedObjectX; out NoisyContours: IHUntypedObjectX; NumRegrPoints: OleVariant; Amp: OleVariant);

简化后为：

** AddNoiseWhiteContourXld( Contours: X; out NoisyContours: X; NumRegrPoints, Amp);

 ** BestMatch( Image: X; TemplateID, MaxError, SubPixel, out Row, out Column, out Error);
 说明,  best_match,寻找一个模板和一个图像的最佳匹配。

 ** BestMatchMg( Image: X; TemplateID, MaxError, SubPixel, NumLevels, WhichLevels, out Row, out Column, out Error);
 说明,  best_match_mg,在金字塔中寻找最佳灰度值匹配。

 ** BestMatchPreMg( ImagePyramid: X; TemplateID, MaxError, SubPixel, NumLevels, WhichLevels, out Row, out Column, out Error);
 说明,  best_match_pre_mg,在预生成的金字塔中寻找最佳灰度值匹配。

 ** BestMatchRot( Image: X; TemplateID, AngleStart, AngleExtend, MaxError, SubPixel, out Row, out Column, out Angle, out Error);
 说明,  best_match_rot,寻找一个模板和一个旋转图像的最佳匹配。

 ** BestMatchRotMg( Image: X; TemplateID, AngleStart, AngleExtend, MaxError, SubPixel, NumLevels, out Row, out Column, out Angle, out Error);
 说明,  best_match_rot_mg,寻找一个模板和一个旋转金字塔的最佳匹配。

 ** ClearAllSurfaceMatchingResults;
 说明,  清除所有表面匹配数据

 ** ClearSurfaceMatchingResult( SurfaceMatchingResultID);
 说明,  清除表面匹配数据

 ** ExhaustiveMatch( Image: X; RegionOfInterest: X; ImageTemplate: X; out ImageMatch: X; Mode);
 说明,  exhaustive_match,模板和图像的匹配。

 ** ExhaustiveMatchMg( Image: X; ImageTemplate: X; out ImageMatch: X; Mode, Level, Threshold);
 说明,  exhaustive_match_mg,在一个分辨率塔式结构中匹配模板和图像。

 ** FastMatch( Image: X; out Matches: X; TemplateID, MaxError);
 说明,  fast_match,寻找一个模板和一个图像的所有好的匹配。

 ** FastMatchMg( Image: X; out Matches: X; TemplateID, MaxError, NumLevel);
 说明,  fast_match_mg,在金字塔中寻找所有好的灰度值匹配。

 ** FindAnisoShapeModel( Image: X; ModelID, AngleStart, AngleExtent, ScaleRMin, ScaleRMax, ScaleCMin, ScaleCMax, MinScore, NumMatches, MaxOverlap, SubPixel, NumLevels, Greediness, out Row, out Column, out Angle, out ScaleR, out ScaleC, out Score);
 说明,  find_aniso_shape_model,在一个图像中找出一个各向异性尺度不变轮廓的最佳匹配。

 ** FindAnisoShapeModels( Image: X; ModelIDs, AngleStart, AngleExtent, ScaleRMin, ScaleRMax, ScaleCMin, ScaleCMax, MinScore, NumMatches, MaxOverlap, SubPixel, NumLevels, Greediness, out Row, out Column, out Angle, out ScaleR, out ScaleC, out Score, out Model);
 说明,  find_aniso_shape_models,找出多重各向异性尺度不变轮廓模型的最佳匹配。

 ** FindCalibDescriptorModel( Image: X; ModelID, DetectorParamName, DetectorParamValue, DescriptorParamName, DescriptorParamValue, MinScore, NumMatches, CamParam, ScoreType, out Pose, out Score);
 说明,  检测校准描述模型

 ** FindComponentModel( Image: X; ComponentModelID, RootComponent, AngleStartRoot, AngleExtentRoot, MinScore, NumMatches, MaxOverlap, IfRootNotFound, IfComponentNotFound, PosePrediction, MinScoreComp, SubPixelComp, NumLevelsComp, GreedinessComp, out ModelStart, out ModelEnd, out Score, out RowComp, out ColumnComp, out AngleComp, out ScoreComp, out ModelComp);
 说明,  find_component_model,在一个图像中找出一个组件模型的最佳匹配。

 ** FindLocalDeformableModel( Image: X; out ImageRectified: X; out VectorField: X; out DeformedContours: X; ModelID, AngleStart, AngleExtent, ScaleRMin, ScaleRMax, ScaleCMin, ScaleCMax, MinScore, NumMatches, MaxOverlap, NumLevels, Greediness, ResultType, ParamName, ParamValue, out Score, out Row, out Column);

 ** FindNccModel( Image: X; ModelID, AngleStart, AngleExtent, MinScore, NumMatches, MaxOverlap, SubPixel, NumLevels, out Row, out Column, out Angle, out Score);
 说明,  find_ncc_model,找出一个图像中的一个NCC模型的最佳匹配。

 ** FindPlanarCalibDeformableModel( Image: X; ModelID, AngleStart, AngleExtent, ScaleRMin, ScaleRMax, ScaleCMin, ScaleCMax, MinScore, NumMatches, MaxOverlap, NumLevels, Greediness, ParamName, ParamValue, out Pose, out CovPose, out Score);
 说明,  检测校准平面变形模型

 ** FindPlanarUncalibDeformableModel( Image: X; ModelID, AngleStart, AngleExtent, ScaleRMin, ScaleRMax, ScaleCMin, ScaleCMax, MinScore, NumMatches, MaxOverlap, NumLevels, Greediness, ParamName, ParamValue, out HomMat2d, out Score);
 说明,  检测无校准平面变形模型

 ** FindScaledShapeModel( Image: X; ModelID, AngleStart, AngleExtent, ScaleMin, ScaleMax, MinScore, NumMatches, MaxOverlap, SubPixel, NumLevels, Greediness, out Row, out Column, out Angle, out Scale, out Score);
 说明,  find_scaled_shape_model,在一个图像中找出一个尺度不变轮廓模型的最佳匹配。

 ** FindScaledShapeModels( Image: X; ModelIDs, AngleStart, AngleExtent, ScaleMin, ScaleMax, MinScore, NumMatches, MaxOverlap, SubPixel, NumLevels, Greediness, out Row, out Column, out Angle, out Scale, out Score, out Model);
 说明,  find_scaled_shape_models,找出多重尺度不变轮廓模型的最佳匹配。

 ** FindShapeModel( Image: X; ModelID, AngleStart, AngleExtent, MinScore, NumMatches, MaxOverlap, SubPixel, NumLevels, Greediness, out Row, out Column, out Angle, out Score);
 说明,  find_shape_model,在一个图像中找出一个轮廓模型的最佳匹配。

 ** FindShapeModels( Image: X; ModelIDs, AngleStart, AngleExtent, MinScore, NumMatches, MaxOverlap, SubPixel, NumLevels, Greediness, out Row, out Column, out Angle, out Score, out Model);
 说明,  find_shape_models,找出多重轮廓模型的最佳匹配。

 ** FindSurfaceModel( SurfaceModelID, ObjectModel3D, RelSamplingDistance, KeyPointFraction, MinScore, ReturnResultHandle, GenParamName, GenParamValue, out Pose, out Score, out SurfaceMatchingResultID);
 说明,  找出表面模型

 ** FindUncalibDescriptorModel( Image: X; ModelID, DetectorParamName, DetectorParamValue, DescriptorParamName, DescriptorParamValue, MinScore, NumMatches, ScoreType, out HomMat2d, out Score);
 说明,  找出无校准平面变形模型

 ** GetFoundComponentModel( out FoundComponents: X; ComponentModelID, ModelStart, ModelEnd, RowComp, ColumnComp, AngleComp, ScoreComp, ModelComp, ModelMatch, MarkOrientation, out RowCompInst, out ColumnCompInst, out AngleCompInst, out ScoreCompInst);
 说明,  get_found_component_model,返回一个组件模型的一个创建例子的组件。

 ** GetSurfaceMatchingResult( SurfaceMatchingResultID, ResultName, ResultIndex, out ResultValue);
 说明,  获取表面匹配结果

 ** MatchEssentialMatrixRansac( Image1: X; Image2: X; Rows1, Cols1, Rows2, Cols2, CamMat1, CamMat2, GrayMatchMethod, MaskSize, RowMove, ColMove, RowTolerance, ColTolerance, Rotation, MatchThreshold, EstimationMethod, DistanceThreshold, RandSeed, out EMatrix, out CovEMat, out Error, out Points1, out Points2);
 说明,  按RANSA算法匹配矩阵

 ** MatchFourierCoeff( RealCoef1, ImaginaryCoef1, RealCoef2, ImaginaryCoef2, MaxCoef, Damping, out Distance);
 说明,  match_fourier_coeff,两个元组的相似性。

 ** MatchFunct1DTrans( Function1, Function2, Border, Params, UseParams, out Params, out ChiSquare, out Covar);
 说明,  match_funct_1d_trans,计算两个函数传递参数。

 ** MatchFundamentalMatrixDistortionRansac( Image1: X; Image2: X; Rows1, Cols1, Rows2, Cols2, GrayMatchMethod, MaskSize, RowMove, ColMove, RowTolerance, ColTolerance, Rotation, MatchThreshold, EstimationMethod, DistanceThreshold, RandSeed, out FMatrix, out Kappa, out Error, out Points1, out Points2);
 说明,  按RANSA算法匹配矩阵，有失真度参数

 ** MatchFundamentalMatrixRansac( Image1: X; Image2: X; Rows1, Cols1, Rows2, Cols2, GrayMatchMethod, MaskSize, RowMove, ColMove, RowTolerance, ColTolerance, Rotation, MatchThreshold, EstimationMethod, DistanceThreshold, RandSeed, out FMatrix, out CovFMat, out Error, out Points1, out Points2);
 说明,  按RANSA算法匹配矩阵，基本匹配

 ** MatchRelPoseRansac( Image1: X; Image2: X; Rows1, Cols1, Rows2, Cols2, CamPar1, CamPar2, GrayMatchMethod, MaskSize, RowMove, ColMove, RowTolerance, ColTolerance, Rotation, MatchThreshold, EstimationMethod, DistanceThreshold, RandSeed, out RelPose, out CovRelPose, out Error, out Points1, out Points2);
 说明,  按RANSA算法匹配相对位置

 ** ProjMatchPointsDistortionRansac( Image1: X; Image2: X; Rows1, Cols1, Rows2, Cols2, GrayMatchMethod, MaskSize, RowMove, ColMove, RowTolerance, ColTolerance, Rotation, MatchThreshold, EstimationMethod, DistanceThreshold, RandSeed, out HomMat2d, out Kappa, out Error, out Points1, out Points2);
 说明,  Ransac算法节点投影失真计算

 ** ProjMatchPointsDistortionRansacGuided( Image1: X; Image2: X; Rows1, Cols1, Rows2, Cols2, GrayMatchMethod, MaskSize, HomMat2dGuide, KappaGuide, DistanceTolerance, MatchThreshold, EstimationMethod, DistanceThreshold, RandSeed, out HomMat2d, out Kappa, out Error, out Points1, out Points2);
 说明,  Ransac引导算法节点投影失真计算

 ** ProjMatchPointsRansac( Image1: X; Image2: X; Rows1, Cols1, Rows2, Cols2, GrayMatchMethod, MaskSize, RowMove, ColMove, RowTolerance, ColTolerance, Rotation, MatchThreshold, EstimationMethod, DistanceThreshold, RandSeed, out HomMat2d, out Points1, out Points2);
 说明,  Ransac算法，投影节点匹配

 ** ProjMatchPointsRansacGuided( Image1: X; Image2: X; Rows1, Cols1, Rows2, Cols2, GrayMatchMethod, MaskSize, HomMat2dGuide, DistanceTolerance, MatchThreshold, EstimationMethod, DistanceThreshold, RandSeed, out HomMat2d, out Points1, out Points2);
 说明,  Ransac引导算法，投影节点匹配

 ** RefineSurfaceModelPose( SurfaceModelID, ObjectModel3D, InitialPose, MinScore, ReturnResultHandle, GenParamName, GenParamValue, out Pose, out Score, out SurfaceMatchingResultID);
 说明,  细化表面模型

 ** SelectMatchingLines( RegionIn: X; out RegionLines: X; AngleIn, DistIn, LineWidth, Thresh, out AngleOut, out DistOut);
 说明,  select_matching_lines,选取HNF中线的集合中匹配区域最好的线。

 ** TupleRegexpMatch( Data, Expression, out Matches);
 说明,  tuple_regexp_match,利用公式提取子链。

 ** TupleRegexpTest( Data, Expression, out NumMatches);
 说明,  tuple_regexp_test,测试一个字符串是否满足一个规则公式的要求。