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《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);

 

  1 ** BestMatch( Image: X; TemplateID, MaxError, SubPixel, out Row, out Column, out Error); 
  2 说明,  best_match,寻找一个模板和一个图像的最佳匹配。
  3 
  4 ** BestMatchMg( Image: X; TemplateID, MaxError, SubPixel, NumLevels, WhichLevels, out Row, out Column, out Error); 
  5 说明,  best_match_mg,在金字塔中寻找最佳灰度值匹配。
  6 
  7 ** BestMatchPreMg( ImagePyramid: X; TemplateID, MaxError, SubPixel, NumLevels, WhichLevels, out Row, out Column, out Error); 
  8 说明,  best_match_pre_mg,在预生成的金字塔中寻找最佳灰度值匹配。
  9 
 10 ** BestMatchRot( Image: X; TemplateID, AngleStart, AngleExtend, MaxError, SubPixel, out Row, out Column, out Angle, out Error); 
 11 说明,  best_match_rot,寻找一个模板和一个旋转图像的最佳匹配。
 12 
 13 ** BestMatchRotMg( Image: X; TemplateID, AngleStart, AngleExtend, MaxError, SubPixel, NumLevels, out Row, out Column, out Angle, out Error); 
 14 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。
 15 
 16 ** ClearAllSurfaceMatchingResults; 
 17 说明,  清除所有表面匹配数据
 18 
 19 ** ClearSurfaceMatchingResult( SurfaceMatchingResultID); 
 20 说明,  清除表面匹配数据
 21 
 22 ** ExhaustiveMatch( Image: X; RegionOfInterest: X; ImageTemplate: X; out ImageMatch: X; Mode); 
 23 说明,  exhaustive_match,模板和图像的匹配。
 24 
 25 ** ExhaustiveMatchMg( Image: X; ImageTemplate: X; out ImageMatch: X; Mode, Level, Threshold); 
 26 说明,  exhaustive_match_mg,在一个分辨率塔式结构中匹配模板和图像。
 27 
 28 ** FastMatch( Image: X; out Matches: X; TemplateID, MaxError); 
 29 说明,  fast_match,寻找一个模板和一个图像的所有好的匹配。
 30 
 31 ** FastMatchMg( Image: X; out Matches: X; TemplateID, MaxError, NumLevel); 
 32 说明,  fast_match_mg,在金字塔中寻找所有好的灰度值匹配。
 33 
 34 ** 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); 
 35 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。
 36 
 37 ** 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); 
 38 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。
 39 
 40 ** FindCalibDescriptorModel( Image: X; ModelID, DetectorParamName, DetectorParamValue, DescriptorParamName, DescriptorParamValue, MinScore, NumMatches, CamParam, ScoreType, out Pose, out Score); 
 41 说明,  检测校准描述模型
 42 
 43 ** 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); 
 44 说明,  find_component_model,在一个图像中找出一个组件模型的最佳匹配。
 45 
 46 ** 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);
 47 
 48 ** FindNccModel( Image: X; ModelID, AngleStart, AngleExtent, MinScore, NumMatches, MaxOverlap, SubPixel, NumLevels, out Row, out Column, out Angle, out Score); 
 49 说明,  find_ncc_model,找出一个图像中的一个NCC模型的最佳匹配。
 50 
 51 ** FindPlanarCalibDeformableModel( Image: X; ModelID, AngleStart, AngleExtent, ScaleRMin, ScaleRMax, ScaleCMin, ScaleCMax, MinScore, NumMatches, MaxOverlap, NumLevels, Greediness, ParamName, ParamValue, out Pose, out CovPose, out Score); 
 52 说明,  检测校准平面变形模型
 53 
 54 ** FindPlanarUncalibDeformableModel( Image: X; ModelID, AngleStart, AngleExtent, ScaleRMin, ScaleRMax, ScaleCMin, ScaleCMax, MinScore, NumMatches, MaxOverlap, NumLevels, Greediness, ParamName, ParamValue, out HomMat2d, out Score); 
 55 说明,  检测无校准平面变形模型
 56 
 57 ** FindScaledShapeModel( Image: X; ModelID, AngleStart, AngleExtent, ScaleMin, ScaleMax, MinScore, NumMatches, MaxOverlap, SubPixel, NumLevels, Greediness, out Row, out Column, out Angle, out Scale, out Score); 
 58 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。
 59 
 60 ** 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); 
 61 说明,  find_scaled_shape_models,找出多重尺度不变轮廓模型的最佳匹配。
 62 
 63 ** FindShapeModel( Image: X; ModelID, AngleStart, AngleExtent, MinScore, NumMatches, MaxOverlap, SubPixel, NumLevels, Greediness, out Row, out Column, out Angle, out Score); 
 64 说明,  find_shape_model,在一个图像中找出一个轮廓模型的最佳匹配。
 65 
 66 ** FindShapeModels( Image: X; ModelIDs, AngleStart, AngleExtent, MinScore, NumMatches, MaxOverlap, SubPixel, NumLevels, Greediness, out Row, out Column, out Angle, out Score, out Model); 
 67 说明,  find_shape_models,找出多重轮廓模型的最佳匹配。
 68 
 69 ** FindSurfaceModel( SurfaceModelID, ObjectModel3D, RelSamplingDistance, KeyPointFraction, MinScore, ReturnResultHandle, GenParamName, GenParamValue, out Pose, out Score, out SurfaceMatchingResultID); 
 70 说明,  找出表面模型
 71 
 72 ** FindUncalibDescriptorModel( Image: X; ModelID, DetectorParamName, DetectorParamValue, DescriptorParamName, DescriptorParamValue, MinScore, NumMatches, ScoreType, out HomMat2d, out Score); 
 73 说明,  找出无校准平面变形模型
 74 
 75 ** GetFoundComponentModel( out FoundComponents: X; ComponentModelID, ModelStart, ModelEnd, RowComp, ColumnComp, AngleComp, ScoreComp, ModelComp, ModelMatch, MarkOrientation, out RowCompInst, out ColumnCompInst, out AngleCompInst, out ScoreCompInst); 
 76 说明,  get_found_component_model,返回一个组件模型的一个创建例子的组件。
 77 
 78 ** GetSurfaceMatchingResult( SurfaceMatchingResultID, ResultName, ResultIndex, out ResultValue); 
 79 说明,  获取表面匹配结果
 80 
 81 ** 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); 
 82 说明,  按RANSA算法匹配矩阵
 83 
 84 ** MatchFourierCoeff( RealCoef1, ImaginaryCoef1, RealCoef2, ImaginaryCoef2, MaxCoef, Damping, out Distance); 
 85 说明,  match_fourier_coeff,两个元组的相似性。
 86 
 87 ** MatchFunct1DTrans( Function1, Function2, Border, Params, UseParams, out Params, out ChiSquare, out Covar); 
 88 说明,  match_funct_1d_trans,计算两个函数传递参数。
 89 
 90 ** 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); 
 91 说明,  按RANSA算法匹配矩阵，有失真度参数
 92 
 93 ** 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); 
 94 说明,  按RANSA算法匹配矩阵，基本匹配
 95 
 96 ** 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); 
 97 说明,  按RANSA算法匹配相对位置
 98 
 99 ** 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); 
100 说明,  Ransac算法节点投影失真计算
101 
102 ** 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); 
103 说明,  Ransac引导算法节点投影失真计算
104 
105 ** 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); 
106 说明,  Ransac算法，投影节点匹配
107 
108 ** ProjMatchPointsRansacGuided( Image1: X; Image2: X; Rows1, Cols1, Rows2, Cols2, GrayMatchMethod, MaskSize, HomMat2dGuide, DistanceTolerance, MatchThreshold, EstimationMethod, DistanceThreshold, RandSeed, out HomMat2d, out Points1, out Points2); 
109 说明,  Ransac引导算法，投影节点匹配
110 
111 ** RefineSurfaceModelPose( SurfaceModelID, ObjectModel3D, InitialPose, MinScore, ReturnResultHandle, GenParamName, GenParamValue, out Pose, out Score, out SurfaceMatchingResultID); 
112 说明,  细化表面模型
113 
114 ** SelectMatchingLines( RegionIn: X; out RegionLines: X; AngleIn, DistIn, LineWidth, Thresh, out AngleOut, out DistOut); 
115 说明,  select_matching_lines,选取HNF中线的集合中匹配区域最好的线。
116 
117 ** TupleRegexpMatch( Data, Expression, out Matches); 
118 说明,  tuple_regexp_match,利用公式提取子链。
119 
120 ** TupleRegexpTest( Data, Expression, out NumMatches); 
121 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。

 

转载于:https://www.cnblogs.com/ziwang/p/4876804.html