find_shape_modelsT_find_shape_modelsFindShapeModelsFindShapeModels (Operator)

Name

find_shape_modelsT_find_shape_modelsFindShapeModelsFindShapeModels — Find the best matches of multiple shape models.

Signature

find_shape_models(Image : : ModelIDs, AngleStart, AngleExtent, MinScore, NumMatches, MaxOverlap, SubPixel, NumLevels, Greediness : Row, Column, Angle, Score, Model)

Herror T_find_shape_models(const Hobject Image, const Htuple ModelIDs, const Htuple AngleStart, const Htuple AngleExtent, const Htuple MinScore, const Htuple NumMatches, const Htuple MaxOverlap, const Htuple SubPixel, const Htuple NumLevels, const Htuple Greediness, Htuple* Row, Htuple* Column, Htuple* Angle, Htuple* Score, Htuple* Model)

void FindShapeModels(const HObject& Image, const HTuple& ModelIDs, const HTuple& AngleStart, const HTuple& AngleExtent, const HTuple& MinScore, const HTuple& NumMatches, const HTuple& MaxOverlap, const HTuple& SubPixel, const HTuple& NumLevels, const HTuple& Greediness, HTuple* Row, HTuple* Column, HTuple* Angle, HTuple* Score, HTuple* Model)

static void HShapeModel::FindShapeModels(const HImage& Image, const HShapeModelArray& ModelIDs, const HTuple& AngleStart, const HTuple& AngleExtent, const HTuple& MinScore, const HTuple& NumMatches, const HTuple& MaxOverlap, const HTuple& SubPixel, const HTuple& NumLevels, const HTuple& Greediness, HTuple* Row, HTuple* Column, HTuple* Angle, HTuple* Score, HTuple* Model)

void HShapeModel::FindShapeModels(const HImage& Image, double AngleStart, double AngleExtent, double MinScore, Hlong NumMatches, double MaxOverlap, const HString& SubPixel, Hlong NumLevels, double Greediness, HTuple* Row, HTuple* Column, HTuple* Angle, HTuple* Score, HTuple* Model) const

void HShapeModel::FindShapeModels(const HImage& Image, double AngleStart, double AngleExtent, double MinScore, Hlong NumMatches, double MaxOverlap, const char* SubPixel, Hlong NumLevels, double Greediness, HTuple* Row, HTuple* Column, HTuple* Angle, HTuple* Score, HTuple* Model) const

void HShapeModel::FindShapeModels(const HImage& Image, double AngleStart, double AngleExtent, double MinScore, Hlong NumMatches, double MaxOverlap, const wchar_t* SubPixel, Hlong NumLevels, double Greediness, HTuple* Row, HTuple* Column, HTuple* Angle, HTuple* Score, HTuple* Model) const   (Windows only)

void HImage::FindShapeModels(const HShapeModelArray& ModelIDs, const HTuple& AngleStart, const HTuple& AngleExtent, const HTuple& MinScore, const HTuple& NumMatches, const HTuple& MaxOverlap, const HTuple& SubPixel, const HTuple& NumLevels, const HTuple& Greediness, HTuple* Row, HTuple* Column, HTuple* Angle, HTuple* Score, HTuple* Model) const

void HImage::FindShapeModels(const HShapeModel& ModelIDs, double AngleStart, double AngleExtent, double MinScore, Hlong NumMatches, double MaxOverlap, const HString& SubPixel, Hlong NumLevels, double Greediness, HTuple* Row, HTuple* Column, HTuple* Angle, HTuple* Score, HTuple* Model) const

void HImage::FindShapeModels(const HShapeModel& ModelIDs, double AngleStart, double AngleExtent, double MinScore, Hlong NumMatches, double MaxOverlap, const char* SubPixel, Hlong NumLevels, double Greediness, HTuple* Row, HTuple* Column, HTuple* Angle, HTuple* Score, HTuple* Model) const

void HImage::FindShapeModels(const HShapeModel& ModelIDs, double AngleStart, double AngleExtent, double MinScore, Hlong NumMatches, double MaxOverlap, const wchar_t* SubPixel, Hlong NumLevels, double Greediness, HTuple* Row, HTuple* Column, HTuple* Angle, HTuple* Score, HTuple* Model) const   (Windows only)

static void HOperatorSet.FindShapeModels(HObject image, HTuple modelIDs, HTuple angleStart, HTuple angleExtent, HTuple minScore, HTuple numMatches, HTuple maxOverlap, HTuple subPixel, HTuple numLevels, HTuple greediness, out HTuple row, out HTuple column, out HTuple angle, out HTuple score, out HTuple model)

static void HShapeModel.FindShapeModels(HImage image, HShapeModel[] modelIDs, HTuple angleStart, HTuple angleExtent, HTuple minScore, HTuple numMatches, HTuple maxOverlap, HTuple subPixel, HTuple numLevels, HTuple greediness, out HTuple row, out HTuple column, out HTuple angle, out HTuple score, out HTuple model)

void HShapeModel.FindShapeModels(HImage image, double angleStart, double angleExtent, double minScore, int numMatches, double maxOverlap, string subPixel, int numLevels, double greediness, out HTuple row, out HTuple column, out HTuple angle, out HTuple score, out HTuple model)

void HImage.FindShapeModels(HShapeModel[] modelIDs, HTuple angleStart, HTuple angleExtent, HTuple minScore, HTuple numMatches, HTuple maxOverlap, HTuple subPixel, HTuple numLevels, HTuple greediness, out HTuple row, out HTuple column, out HTuple angle, out HTuple score, out HTuple model)

void HImage.FindShapeModels(HShapeModel modelIDs, double angleStart, double angleExtent, double minScore, int numMatches, double maxOverlap, string subPixel, int numLevels, double greediness, out HTuple row, out HTuple column, out HTuple angle, out HTuple score, out HTuple model)

Description

The operator find_shape_modelsfind_shape_modelsFindShapeModelsFindShapeModelsFindShapeModels finds the best NumMatchesNumMatchesNumMatchesNumMatchesnumMatches instances of the shape models that are passed in the tuple ModelIDsModelIDsModelIDsModelIDsmodelIDs in the input image ImageImageImageImageimage. The models must have been created previously by calling create_shape_modelcreate_shape_modelCreateShapeModelCreateShapeModelCreateShapeModel or read_shape_modelread_shape_modelReadShapeModelReadShapeModelReadShapeModel. In contrast to find_shape_modelfind_shape_modelFindShapeModelFindShapeModelFindShapeModel, multiple models can be searched in the same image in one call.

The position and rotation of the found instances of the model is returned in RowRowRowRowrow, ColumnColumnColumnColumncolumn, and AngleAngleAngleAngleangle. The score of each found instance is returned in ScoreScoreScoreScorescore. The type of the found instances of the models is returned in ModelModelModelModelmodel. For details see respective sections below.

Characteristics of the parameter semantics

Compared to find_shape_modelfind_shape_modelFindShapeModelFindShapeModelFindShapeModel, the semantics of all input parameters have changed to some extent. All input parameters must either contain one element, in which case the parameter is used for all models, or must contain the same number of elements as ModelIDsModelIDsModelIDsModelIDsmodelIDs, in which case each parameter element refers to the corresponding element in ModelIDsModelIDsModelIDsModelIDsmodelIDs. (NumLevelsNumLevelsNumLevelsNumLevelsnumLevels may also contain either two or twice the number of elements as ModelIDsModelIDsModelIDsModelIDsmodelIDs.) More details can be found below in the sections containing information for the respective parameters. Note that a call to find_shape_modelsfind_shape_modelsFindShapeModelsFindShapeModelsFindShapeModels with multiple values for ModelIDsModelIDsModelIDsModelIDsmodelIDs, NumMatchesNumMatchesNumMatchesNumMatchesnumMatches and MaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlap has the same effect as multiple independent calls to find_shape_modelfind_shape_modelFindShapeModelFindShapeModelFindShapeModel with the respective parameters. However, a single call to find_shape_modelsfind_shape_modelsFindShapeModelsFindShapeModelsFindShapeModels is considerably more efficient.

Input parameters in detail

The image and its domain:

The domain of the ImageImageImageImageimage determines the search space for the reference point of the model, i.e., for the center of gravity of the domain (region) of the image that was used to create the shape model with create_shape_modelcreate_shape_modelCreateShapeModelCreateShapeModelCreateShapeModel. A different origin set with set_shape_model_originset_shape_model_originSetShapeModelOriginSetShapeModelOriginSetShapeModelOrigin is not taken into account. The model is searched within those points of the domain of the image, in which the model lies completely within the image. This means that the model will not be found if it extends beyond the borders of the image, even if it would achieve a score greater than MinScoreMinScoreMinScoreMinScoreminScore (see below). Note that, if for a certain pyramid level the model touches the image border, it might not be found even if it lies completely within the original image. As a rule of thumb, the model might not be found if its distance to an image border falls below . This behavior can be changed with set_system('border_shape_models','true')set_system("border_shape_models","true")SetSystem("border_shape_models","true")SetSystem("border_shape_models","true")SetSystem("border_shape_models","true") for all models or with set_shape_model_param(ModelID, 'border_shape_models','true')set_shape_model_param(ModelID, "border_shape_models","true")SetShapeModelParam(ModelID, "border_shape_models","true")SetShapeModelParam(ModelID, "border_shape_models","true")SetShapeModelParam(ModelID, "border_shape_models","true") for a specific model, which will cause models that extend beyond the image border to be found if they achieve a score greater than MinScoreMinScoreMinScoreMinScoreminScore. Here, points lying outside the image are regarded as being occluded, i.e., they lower the score. It should be noted that the runtime of the search will increase in this mode. Note further, that in rare cases, which occur typically only for artificial images, the model might not be found also if for certain pyramid levels the model touches the border of the reduced domain. Then, it may help to enlarge the reduced domain by using, e.g., dilation_circledilation_circleDilationCircleDilationCircleDilationCircle.

As usual, the domain of the input ImageImageImageImageimage is used to restrict the search space for the reference point of the models ModelIDsModelIDsModelIDsModelIDsmodelIDs. Consistent with the above semantics, the input ImageImageImageImageimage can therefore contain a single image object or an image object tuple containing multiple image objects. If ImageImageImageImageimage contains a single image object, its domain is used as the region of interest for all models in ModelIDsModelIDsModelIDsModelIDsmodelIDs. If ImageImageImageImageimage contains multiple image objects, each domain is used as the region of interest for the corresponding model in ModelIDsModelIDsModelIDsModelIDsmodelIDs. In this case, the images have to be identical except for their domains, i.e., ImageImageImageImageimage cannot be constructed in an arbitrary manner using concat_objconcat_objConcatObjConcatObjConcatObj, but must be created from the same image using add_channelsadd_channelsAddChannelsAddChannelsAddChannels or equivalent calls. If this is not the case, an error message is returned.

AngleStart and AngleExtent:

The parameters AngleStartAngleStartAngleStartAngleStartangleStart and AngleExtentAngleExtentAngleExtentAngleExtentangleExtent determine the range of rotations for which the model is searched. If necessary, the range of rotations is clipped to the range given when the model was created with create_shape_modelcreate_shape_modelCreateShapeModelCreateShapeModelCreateShapeModel. In particular, this means that the angle ranges of the model and the search must overlap.

Note that in some cases instances with a rotation that is slightly outside the specified range are found. This may happen if the specified range is smaller than the range given during the creation of the model. AngleStartAngleStartAngleStartAngleStartangleStart and AngleExtentAngleExtentAngleExtentAngleExtentangleExtent are checked only at the highest pyramid level. Matches that are found on the highest pyramid level are refined to the lowest pyramid level. For performance reasons, however, during the refinement it is no longer checked whether the matches are still within the specified range.

MinScore:

The parameter MinScoreMinScoreMinScoreMinScoreminScore determines what score a potential match must at least have to be regarded as an instance of the model in the image. The larger MinScoreMinScoreMinScoreMinScoreminScore is chosen, the faster the search is. If the model can be expected never to be occluded in the images, MinScoreMinScoreMinScoreMinScoreminScore may be set as high as 0.8 or even 0.9. If the matches are not tracked to the lowest pyramid level (see below) it might happen that instances with a score slightly below MinScoreMinScoreMinScoreMinScoreminScore are found.

NumMatches:

The maximum number of instances to be found can be determined with NumMatchesNumMatchesNumMatchesNumMatchesnumMatches. If more than NumMatchesNumMatchesNumMatchesNumMatchesnumMatches instances with a score greater than MinScoreMinScoreMinScoreMinScoreminScore are found in the image, only the best NumMatchesNumMatchesNumMatchesNumMatchesnumMatches instances are returned. If fewer than NumMatchesNumMatchesNumMatchesNumMatchesnumMatches are found, only that number is returned, i.e., the parameter MinScoreMinScoreMinScoreMinScoreminScore takes precedence over NumMatchesNumMatchesNumMatchesNumMatchesnumMatches. If all model instances exceeding MinScoreMinScoreMinScoreMinScoreminScore in the image should be found, NumMatchesNumMatchesNumMatchesNumMatchesnumMatches must be set to 0.

When tracking the matches through the image pyramid, on each level, some less promising matches are rejected based on NumMatchesNumMatchesNumMatchesNumMatchesnumMatches. Thus, it is possible that some matches are rejected that would have had a higher score on the lowest pyramid level. Due to this, for example, the found match for NumMatchesNumMatchesNumMatchesNumMatchesnumMatches set to 1 might be different from the match with the highest score returned when setting NumMatchesNumMatchesNumMatchesNumMatchesnumMatches to 0 or > 1.

If multiple objects with a similar score are expected, but only the one with the highest score should be returned, it might be preferable to raise NumMatchesNumMatchesNumMatchesNumMatchesnumMatches, and then select the match with the highest score.

If NumMatchesNumMatchesNumMatchesNumMatchesnumMatches contains one element, find_shape_modelsfind_shape_modelsFindShapeModelsFindShapeModelsFindShapeModels returns the best NumMatchesNumMatchesNumMatchesNumMatchesnumMatches instances of the model irrespective of the type of the model. If, for example, two models are passed in ModelIDsModelIDsModelIDsModelIDsmodelIDs and NumMatchesNumMatchesNumMatchesNumMatchesnumMatches = 2 is selected, it can happen that two instances of the first model and no instances of the second model, one instance of the first model and one instance of the second model, or no instances of the first model and two instances of the second model are returned. If, on the other hand, NumMatchesNumMatchesNumMatchesNumMatchesnumMatches contains multiple values, the number of instances returned of the different models corresponds to the number specified in the respective entry in NumMatchesNumMatchesNumMatchesNumMatchesnumMatches. If, for example, NumMatchesNumMatchesNumMatchesNumMatchesnumMatches = [1,1] is selected, one instance of the first model and one instance of the second model is returned.

MaxOverlap:

If the model exhibits symmetries it may happen that multiple instances with similar positions but different rotations are found in the image. The parameter MaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlap determines by what fraction (i.e., a number between 0 and 1) two instances may at most overlap in order to consider them as different instances, and hence to be returned separately. If two instances overlap each other by more than MaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlap only the best instance is returned. The calculation of the overlap is based on the smallest enclosing rectangle of arbitrary orientation (see smallest_rectangle2smallest_rectangle2SmallestRectangle2SmallestRectangle2SmallestRectangle2) of the found instances. If MaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlap=0, the found instances may not overlap at all, while for MaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlap=1 all instances are returned.

If a single value is passed in MaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlap, the overlap is computed for all found instances of the different models, irrespective of the model type, i.e., instances of the same or of different models that overlap too much are eliminated. If, on the other hand, multiple values are passed in MaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlap, the overlap is only computed for found instances of the model that have the same model type, i.e., only instances of the same model that overlap too much are eliminated. In this mode, models of different types may overlap completely.

SubPixel:

The parameter SubPixelSubPixelSubPixelSubPixelsubPixel determines whether the instances should be extracted with subpixel accuracy. If SubPixelSubPixelSubPixelSubPixelsubPixel is set to 'none'"none""none""none""none" (or 'false'"false""false""false""false" for backwards compatibility) the model's pose is only determined with pixel accuracy and the angle resolution that was specified with create_shape_modelcreate_shape_modelCreateShapeModelCreateShapeModelCreateShapeModel. If SubPixelSubPixelSubPixelSubPixelsubPixel is set to 'interpolation'"interpolation""interpolation""interpolation""interpolation" (or 'true'"true""true""true""true") the position as well as the rotation are determined with subpixel accuracy. In this mode, the model's pose is interpolated from the score function. This mode costs almost no computation time and achieves an accuracy that is high enough for most applications. In some applications, however, the accuracy requirements are extremely high. In these cases, the model's pose can be determined through a least-squares adjustment, i.e., by minimizing the distances of the model points to their corresponding image points. In contrast to 'interpolation'"interpolation""interpolation""interpolation""interpolation", this mode requires additional computation time. The different modes for least-squares adjustment ('least_squares'"least_squares""least_squares""least_squares""least_squares", 'least_squares_high'"least_squares_high""least_squares_high""least_squares_high""least_squares_high", and 'least_squares_very_high'"least_squares_very_high""least_squares_very_high""least_squares_very_high""least_squares_very_high") can be used to determine the accuracy with which the minimum distance is being searched. The higher the accuracy is chosen, the longer the subpixel extraction will take, however. Usually, SubPixelSubPixelSubPixelSubPixelsubPixel should be set to 'interpolation'"interpolation""interpolation""interpolation""interpolation". If least-squares adjustment is desired, 'least_squares'"least_squares""least_squares""least_squares""least_squares" should be chosen because this results in the best trade-off between runtime and accuracy.

Objects that are slightly deformed with respect to the model, in some cases cannot be found or are found but only with a low accuracy. For such objects it is possible to additionally pass a maximal allowable object deformation in the parameter SubPixelSubPixelSubPixelSubPixelsubPixel. The deformation must be specified in pixels. This can be done by passing the optional parameter value 'max_deformation '"max_deformation ""max_deformation ""max_deformation ""max_deformation " followed by an integer value between 0 and 32 (in the same string), which specifies the maximum deformation. For example, if the shape of the object may be deformed by up to 2 pixels with respect to the shape that is stored in the model, the value 'max_deformation 2'"max_deformation 2""max_deformation 2""max_deformation 2""max_deformation 2" must be passed in SubPixelSubPixelSubPixelSubPixelsubPixel in addition to the above described mode for the subpixel extraction, i.e., for example ['least_squares', 'max_deformation 2']["least_squares", "max_deformation 2"]["least_squares", "max_deformation 2"]["least_squares", "max_deformation 2"]["least_squares", "max_deformation 2"]. Passing the value 'max_deformation 0'"max_deformation 0""max_deformation 0""max_deformation 0""max_deformation 0" corresponds to a search without allowing deformations, i.e., the behavior is the same as if no 'max_deformation '"max_deformation ""max_deformation ""max_deformation ""max_deformation " is passed. Note that higher values for the maximum deformation often result in an increased runtime. Furthermore, the higher the deformation value is chosen, the higher is the risk of finding wrong model instances. Both problems mainly arise when searching for small objects or for objects with fine structures. This is because such kinds of objects for higher deformations lose their characteristic shape, which is important for a robust search. Also note that for higher deformations the accuracy of partially occluded objects might decrease if clutter is present close to the object. Consequently, the maximum deformation should be chosen as small as possible and only as high as necessary. Approximately rotationally symmetric objects may not be found if 'max_deformation'"max_deformation""max_deformation""max_deformation""max_deformation" and AngleExtentAngleExtentAngleExtentAngleExtentangleExtent are both set to a value greater than 0. In that case, ambiguities may occur that cannot be resolved, and the match is rejected as false. If this happens, try to set either 'max_deformation'"max_deformation""max_deformation""max_deformation""max_deformation" or AngleExtentAngleExtentAngleExtentAngleExtentangleExtent to 0, or adjust the model such that symmetries are reduced. When specifying a deformation higher than 0 the computation of the score depends on the chosen value for the subpixel extraction. In most cases, the score of a match changes if 'least_squares'"least_squares""least_squares""least_squares""least_squares", 'least_squares_high'"least_squares_high""least_squares_high""least_squares_high""least_squares_high", or 'least_squares_very_high'"least_squares_very_high""least_squares_very_high""least_squares_very_high""least_squares_very_high" (see above) is chosen for the subpixel extraction (in comparison to 'none'"none""none""none""none" or 'interpolation'"interpolation""interpolation""interpolation""interpolation"). Furthermore, if one of the least-squares adjustments is selected the score might increase when increasing the maximum deformation because then for the model points more corresponding image points can be found. To get a meaningful score value and to avoid erroneous matches, we recommend to always combine the allowance of a deformation with a least-squares adjustment.

If the subpixel extraction and/or the maximum object deformation is specified separately for each model, for each model passed in ModelIDsModelIDsModelIDsModelIDsmodelIDs exactly one value for the subpixel extraction must be passed in SubPixelSubPixelSubPixelSubPixelsubPixel. After each value for the subpixel extraction optionally a second value can be passed, which describes the maximum object deformation of the corresponding mode. If for a certain model no value for the maximum object deformation is passed, the model is searched without taking deformations into account. For example, if two models are passed in ModelIDsModelIDsModelIDsModelIDsmodelIDs and for the first model the subpixel extraction is set to 'interpolation'"interpolation""interpolation""interpolation""interpolation" and no object deformations are allowed and for the second model the subpixel extraction is set to 'least_squares'"least_squares""least_squares""least_squares""least_squares" and a maximum object deformation of 3 pixels is allowed, then the tuple ['interpolation', 'least_squares', 'max_deformation 3']["interpolation", "least_squares", "max_deformation 3"]["interpolation", "least_squares", "max_deformation 3"]["interpolation", "least_squares", "max_deformation 3"]["interpolation", "least_squares", "max_deformation 3"] must be passed in SubPixelSubPixelSubPixelSubPixelsubPixel. Alternatively, the equivalent tuple ['interpolation', 'max_deformation 0', 'least_squares', 'max_deformation 3']["interpolation", "max_deformation 0", "least_squares", "max_deformation 3"]["interpolation", "max_deformation 0", "least_squares", "max_deformation 3"]["interpolation", "max_deformation 0", "least_squares", "max_deformation 3"]["interpolation", "max_deformation 0", "least_squares", "max_deformation 3"] may be passed.

NumLevels:

The number of pyramid levels used during the search is determined with NumLevelsNumLevelsNumLevelsNumLevelsnumLevels. If necessary, the number of levels is clipped to the range given when the shape model was created with create_shape_modelcreate_shape_modelCreateShapeModelCreateShapeModelCreateShapeModel. If NumLevelsNumLevelsNumLevelsNumLevelsnumLevels is set to 0, the number of pyramid levels specified in create_shape_modelcreate_shape_modelCreateShapeModelCreateShapeModelCreateShapeModel is used.

In certain cases, the number of pyramid levels that was determined automatically with, for example, create_shape_modelcreate_shape_modelCreateShapeModelCreateShapeModelCreateShapeModel may be too high. The consequence may be that some matches that may have a high final score are rejected on the highest pyramid level and thus are not found. Instead of setting MinScoreMinScoreMinScoreMinScoreminScore to a very low value to find all matches, it may be better to query the value of NumLevelsNumLevelsNumLevelsNumLevelsnumLevels with get_shape_model_paramsget_shape_model_paramsGetShapeModelParamsGetShapeModelParamsGetShapeModelParams and then use a slightly lower value in find_shape_modelsfind_shape_modelsFindShapeModelsFindShapeModelsFindShapeModels. This approach is often better regarding the speed and robustness of the matching.

Optionally, NumLevelsNumLevelsNumLevelsNumLevelsnumLevels can contain a second value that determines the lowest pyramid level to which the found matches are tracked. Hence, a value of [4,2] for NumLevelsNumLevelsNumLevelsNumLevelsnumLevels means that the matching starts at the fourth pyramid level and tracks the matches to the second lowest pyramid level (the lowest pyramid level is denoted by a value of 1). This mechanism can be used to decrease the runtime of the matching. It should be noted, however, that in general the accuracy of the extracted pose parameters is lower in this mode than in the normal mode, in which the matches are tracked to the lowest pyramid level. Hence, if a high accuracy is desired, SubPixelSubPixelSubPixelSubPixelsubPixel should be set to at least 'least_squares'"least_squares""least_squares""least_squares""least_squares". If the lowest pyramid level to use is chosen too large, it may happen that the desired accuracy cannot be achieved, or that wrong instances of the model are found because the model is not specific enough on the higher pyramid levels to facilitate a reliable selection of the correct instance of the model. In this case, the lowest pyramid level to use must be set to a smaller value.

If the lowest pyramid level is specified separately for each model, NumLevelsNumLevelsNumLevelsNumLevelsnumLevels must contain twice the number of elements as ModelIDsModelIDsModelIDsModelIDsmodelIDs. In this case, the number of pyramid levels and the lowest pyramid level must be specified interleaved in NumLevelsNumLevelsNumLevelsNumLevelsnumLevels. If, for example, two models are specified in ModelIDsModelIDsModelIDsModelIDsmodelIDs, the number of pyramid levels is 5 for the first model and 4 for the second model, and the lowest pyramid level is 2 for the first model and 1 for the second model, NumLevelsNumLevelsNumLevelsNumLevelsnumLevels = [5,2,4,1] must be selected. If exactly two models are specified in ModelIDsModelIDsModelIDsModelIDsmodelIDs, a special case occurs. If in this case the lowest pyramid level is to be specified, the number of pyramid levels and the lowest pyramid level must be specified explicitly for both models, even if they are identical, because specifying two values in NumLevelsNumLevelsNumLevelsNumLevelsnumLevels is interpreted as the explicit specification of the number of pyramid levels for the two models.

In input images of poor quality, i.e., in images that are, e.g., defocused, deformed, or noisy, often no instances of the shape model can be found on the lowest pyramid level. The reason for this behavior is the missing or deformed edge information which is a result of the poor image quality. Nevertheless, the edge information may be sufficient on higher pyramid levels. But keep in mind the above mentioned restrictions on accuracy and robustness if instances that were found on higher pyramid levels are used. The selection of the suitable pyramid level, i.e., the lowest pyramid level on which at least one instance of the shape model can be found, depends on the model and on the input image. This pyramid level may vary from image to image. To facilitate the matching on images of poor quality, the lowest pyramid level on which at least one instance of the model can be found can be determined automatically during the matching. To activate this mechanism, i.e., to use the so-called 'increased tolerance mode', the lowest pyramid level must be specified negatively in NumLevelsNumLevelsNumLevelsNumLevelsnumLevels. If, e.g., NumLevelsNumLevelsNumLevelsNumLevelsnumLevels is set to [5,2,4,-1], the lowest pyramid level for the first model is set to 2. If no instance of the first model can be found on this pyramid level, no result will be returned for this model. For the second shape model, the lowest pyramid level is set to -1. Therefore, an instance of the shape model is searched on the pyramid level 1. If no instance of the second model can be found on this pyramid level, the lowest pyramid level is determined on which at least one instance of the model can be found. The instances of this pyramid level will then be returned.

Greediness:

The parameter GreedinessGreedinessGreedinessGreedinessgreediness determines how “greedily” the search should be carried out. If GreedinessGreedinessGreedinessGreedinessgreediness=0, a safe search heuristic is used, which always finds the model if it is visible in the image and the other parameters are set appropriately. However, the search will be relatively time consuming in this case. If GreedinessGreedinessGreedinessGreedinessgreediness=1, an unsafe search heuristic is used, which may cause the model not to be found in rare cases, even though it is visible in the image. For GreedinessGreedinessGreedinessGreedinessgreediness=1, the maximum search speed is achieved. In almost all cases, the shape model will always be found for GreedinessGreedinessGreedinessGreedinessgreediness=0.9.

Output parameters in detail

Row, Column and Angle:

The position and rotation of the found instances of the model is returned in RowRowRowRowrow, ColumnColumnColumnColumncolumn, and AngleAngleAngleAngleangle. The coordinates RowRowRowRowrow and ColumnColumnColumnColumncolumn are the coordinates of the origin of the shape model in the search image. By default, the origin is the center of gravity of the domain (region) of the image that was used to create the shape model with create_shape_modelcreate_shape_modelCreateShapeModelCreateShapeModelCreateShapeModel. A different origin can be set with set_shape_model_originset_shape_model_originSetShapeModelOriginSetShapeModelOriginSetShapeModelOrigin.

Note that the coordinates RowRowRowRowrow and ColumnColumnColumnColumncolumn do not exactly correspond to the position of the model in the search image. Thus, you cannot directly use them. Instead, the values are optimized for creating the transformation matrix with which you can use the results of the matching for various tasks, e.g., to align ROIs for other processing steps. The example given for find_shape_modelfind_shape_modelFindShapeModelFindShapeModelFindShapeModel shows how to create this matrix and use it to display the model at the found position in the search image.

Note also that for visualizing the model at the found position, also the procedure dev_display_shape_matching_results can be used.

Score:

The score of each found instance is returned in ScoreScoreScoreScorescore. The score is a number between 0 and 1, which is an approximate measure of how much of the model is visible in the image. If, for example, half of the model is occluded, the score cannot exceed 0.5.

Model:

The type of the found instances of the models is returned in ModelModelModelModelmodel. The elements of ModelModelModelModelmodel are indices into the tuple ModelIDsModelIDsModelIDsModelIDsmodelIDs, i.e., they can contain values from 0 to |ModelIDsModelIDsModelIDsModelIDsmodelIDs|-1. Hence, a value of 0 in an element of ModelModelModelModelmodel corresponds to an instance of the first model in ModelIDsModelIDsModelIDsModelIDsmodelIDs.

Specifying a timeout

Using the operator set_shape_model_paramset_shape_model_paramSetShapeModelParamSetShapeModelParamSetShapeModelParam you can specify a 'timeout'"timeout""timeout""timeout""timeout" for find_shape_modelsfind_shape_modelsFindShapeModelsFindShapeModelsFindShapeModels. If the shape models referenced by ModelIDsModelIDsModelIDsModelIDsmodelIDs hold different values for 'timeout'"timeout""timeout""timeout""timeout", find_shape_modelsfind_shape_modelsFindShapeModelsFindShapeModelsFindShapeModels uses the smallest one. If find_shape_modelsfind_shape_modelsFindShapeModelsFindShapeModelsFindShapeModels reaches this 'timeout'"timeout""timeout""timeout""timeout", it terminates without results and returns the error code 9400 (H_ERR_TIMEOUT).

MinContrast with multiple models

Please note, that the different models that are given with the parameter ModelIDsModelIDsModelIDsModelIDsmodelIDs should have been created with the same value of MinContrastMinContrastMinContrastMinContrastminContrast. If they were created with different values for MinContrastMinContrastMinContrastMinContrastminContrast, find_shape_modelsfind_shape_modelsFindShapeModelsFindShapeModelsFindShapeModels will use the smallest of these values.

Visualization of the results

To display the results found by shape-based matching, we highly recommend the usage of the procedure dev_display_shape_matching_results.

Further Information

For an explanation of the different 2D coordinate systems used in HALCON, see the introduction of chapter Transformations / 2D Transformations.

Execution Information

This operator supports cancelling timeouts and interrupts.

Parameters

ImageImageImageImageimage (input_object)  (multichannel-)image(-array) objectHImageHImageHobject (byte / uint2)

Input image in which the models should be found.

ModelIDsModelIDsModelIDsModelIDsmodelIDs (input_control)  shape_model(-array) HShapeModel, HTupleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

Handle of the models.

AngleStartAngleStartAngleStartAngleStartangleStart (input_control)  angle.rad(-array) HTupleHTupleHtuple (real) (double) (double) (double)

Smallest rotation of the models.

Default value: -0.39

Suggested values: -3.14, -1.57, -0.79, -0.39, -0.20, 0.0

AngleExtentAngleExtentAngleExtentAngleExtentangleExtent (input_control)  angle.rad(-array) HTupleHTupleHtuple (real) (double) (double) (double)

Extent of the rotation angles.

Default value: 0.79

Suggested values: 6.29, 3.14, 1.57, 0.79, 0.39, 0.0

Restriction: AngleExtent >= 0

MinScoreMinScoreMinScoreMinScoreminScore (input_control)  real(-array) HTupleHTupleHtuple (real) (double) (double) (double)

Minimum score of the instances of the models to be found.

Default value: 0.5

Suggested values: 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0

Typical range of values: 0 ≤ MinScore MinScore MinScore MinScore minScore ≤ 1

Minimum increment: 0.01

Recommended increment: 0.05

NumMatchesNumMatchesNumMatchesNumMatchesnumMatches (input_control)  integer(-array) HTupleHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Number of instances of the models to be found (or 0 for all matches).

Default value: 1

Suggested values: 0, 1, 2, 3, 4, 5, 10, 20

MaxOverlapMaxOverlapMaxOverlapMaxOverlapmaxOverlap (input_control)  real(-array) HTupleHTupleHtuple (real) (double) (double) (double)

Maximum overlap of the instances of the models to be found.

Default value: 0.5

Suggested values: 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0

Typical range of values: 0 ≤ MaxOverlap MaxOverlap MaxOverlap MaxOverlap maxOverlap ≤ 1

Minimum increment: 0.01

Recommended increment: 0.05

SubPixelSubPixelSubPixelSubPixelsubPixel (input_control)  string(-array) HTupleHTupleHtuple (string) (string) (HString) (char*)

Subpixel accuracy if not equal to 'none'"none""none""none""none".

Default value: 'least_squares' "least_squares" "least_squares" "least_squares" "least_squares"

Suggested values: 'none'"none""none""none""none", 'interpolation'"interpolation""interpolation""interpolation""interpolation", 'least_squares'"least_squares""least_squares""least_squares""least_squares", 'least_squares_high'"least_squares_high""least_squares_high""least_squares_high""least_squares_high", 'least_squares_very_high'"least_squares_very_high""least_squares_very_high""least_squares_very_high""least_squares_very_high", 'max_deformation 1'"max_deformation 1""max_deformation 1""max_deformation 1""max_deformation 1", 'max_deformation 2'"max_deformation 2""max_deformation 2""max_deformation 2""max_deformation 2", 'max_deformation 3'"max_deformation 3""max_deformation 3""max_deformation 3""max_deformation 3", 'max_deformation 4'"max_deformation 4""max_deformation 4""max_deformation 4""max_deformation 4", 'max_deformation 5'"max_deformation 5""max_deformation 5""max_deformation 5""max_deformation 5", 'max_deformation 6'"max_deformation 6""max_deformation 6""max_deformation 6""max_deformation 6"

NumLevelsNumLevelsNumLevelsNumLevelsnumLevels (input_control)  integer(-array) HTupleHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Number of pyramid levels used in the matching (and lowest pyramid level to use if |NumLevelsNumLevelsNumLevelsNumLevelsnumLevels| = 2).

Default value: 0

List of values: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10

GreedinessGreedinessGreedinessGreedinessgreediness (input_control)  real(-array) HTupleHTupleHtuple (real) (double) (double) (double)

“Greediness” of the search heuristic (0: safe but slow; 1: fast but matches may be missed).

Default value: 0.9

Suggested values: 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0

Typical range of values: 0 ≤ Greediness Greediness Greediness Greediness greediness ≤ 1

Minimum increment: 0.01

Recommended increment: 0.05

RowRowRowRowrow (output_control)  point.y-array HTupleHTupleHtuple (real) (double) (double) (double)

Row coordinate of the found instances of the models.

ColumnColumnColumnColumncolumn (output_control)  point.x-array HTupleHTupleHtuple (real) (double) (double) (double)

Column coordinate of the found instances of the models.

AngleAngleAngleAngleangle (output_control)  angle.rad-array HTupleHTupleHtuple (real) (double) (double) (double)

Rotation angle of the found instances of the models.

ScoreScoreScoreScorescore (output_control)  real-array HTupleHTupleHtuple (real) (double) (double) (double)

Score of the found instances of the models.

ModelModelModelModelmodel (output_control)  integer-array HTupleHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Index of the found instances of the models.

Example (HDevelop)

read_image (Image, 'pcb_focus/pcb_focus_telecentric_061')
gen_rectangle1 (ROI_0, 236, 241, 313, 321)
gen_circle (ROI_1, 281, 653, 41)
reduce_domain (Image, ROI_0, ImageReduced1)
reduce_domain (Image, ROI_1, ImageReduced2)

create_shape_model (ImageReduced1, 0, rad(-45), rad(180), 0, \
                    'none', 'use_polarity', 30, 10, ModelID1)
create_shape_model (ImageReduced2, 0, rad(-45), rad(180), 0, \
                    'none', 'use_polarity', 30, 10, ModelID2)
ModelIDs:=[ModelID1, ModelID2]
find_shape_models (Image, ModelIDs, rad(-45), rad(90), 0.7, [1,1], 0.5, \
                 'least_squares', 0, 1, Row, Column, Angle, Score, Model)
* Display results
dev_display_shape_matching_results (ModelIDs, 'red', Row, Column, Angle, \
                                    1, 1, Model)

Result

If the parameter values are correct, the operator find_shape_modelsfind_shape_modelsFindShapeModelsFindShapeModelsFindShapeModels returns the value 2 (H_MSG_TRUE). If the input is empty (no input images are available) the behavior can be set via set_system('no_object_result',<Result>)set_system("no_object_result",<Result>)SetSystem("no_object_result",<Result>)SetSystem("no_object_result",<Result>)SetSystem("no_object_result",<Result>). If necessary, an exception is raised.

Possible Predecessors

add_channelsadd_channelsAddChannelsAddChannelsAddChannels, create_shape_modelcreate_shape_modelCreateShapeModelCreateShapeModelCreateShapeModel, read_shape_modelread_shape_modelReadShapeModelReadShapeModelReadShapeModel, set_shape_model_originset_shape_model_originSetShapeModelOriginSetShapeModelOriginSetShapeModelOrigin, set_shape_model_paramset_shape_model_paramSetShapeModelParamSetShapeModelParamSetShapeModelParam

Possible Successors

clear_shape_modelclear_shape_modelClearShapeModelClearShapeModelClearShapeModel

Alternatives

find_scaled_shape_modelsfind_scaled_shape_modelsFindScaledShapeModelsFindScaledShapeModelsFindScaledShapeModels, find_aniso_shape_modelsfind_aniso_shape_modelsFindAnisoShapeModelsFindAnisoShapeModelsFindAnisoShapeModels, find_shape_modelfind_shape_modelFindShapeModelFindShapeModelFindShapeModel, find_scaled_shape_modelfind_scaled_shape_modelFindScaledShapeModelFindScaledShapeModelFindScaledShapeModel, find_aniso_shape_modelfind_aniso_shape_modelFindAnisoShapeModelFindAnisoShapeModelFindAnisoShapeModel, find_ncc_modelfind_ncc_modelFindNccModelFindNccModelFindNccModel, find_ncc_modelsfind_ncc_modelsFindNccModelsFindNccModelsFindNccModels

See also

set_systemset_systemSetSystemSetSystemSetSystem, get_systemget_systemGetSystemGetSystemGetSystem

Module

Matching