create_ncc_model — Prepare an NCC model for matching.
The operator create_ncc_model prepares a template, which is passed in the image Template, as an NCC model used for matching using the normalized cross correlation (NCC). The ROI of the model is passed as the domain of Template.
The model is generated using multiple image pyramid levels at multiple rotations on each level and is stored in memory. The output parameter ModelID is a handle for this model, which is used in subsequent calls to find_ncc_model.
The number of pyramid levels is determined with the parameter NumLevels. It should be chosen as large as possible because by this the time necessary to find the object is significantly reduced. On the other hand, NumLevels must be chosen such that the model is still recognizable and contains a sufficient number of points (at least eight) on the highest pyramid level. This can be checked using the domains of the output images of gen_gauss_pyramid. If not enough model points are generated, the number of pyramid levels is reduced internally until enough model points are found on the highest pyramid level. If this procedure would lead to a model with no pyramid levels, i.e., if the number of model points is already too small on the lowest pyramid level, create_ncc_model returns an error message. If NumLevels is set to 'auto' or 0, create_ncc_model determines the number of pyramid levels automatically. The automatically computed number of pyramid levels can be queried using get_ncc_model_params. In rare cases, it might happen that create_ncc_model determines a value for the number of pyramid levels that is too large or too small. If the number of pyramid levels is chosen too large, the model may not be recognized in the image or it may be necessary to select very low parameters for MinScore in find_ncc_model in order to find the model. If the number of pyramid levels is chosen too small, the time required to find the model in find_ncc_model may increase. In these cases, the number of pyramid levels should be selected by inspecting the output of gen_gauss_pyramid. Here, Mode = 'constant' and Scale = 0.5 should be used.
The parameters AngleStart and AngleExtent determine the range of possible rotations, in which the model can occur in the image. Note that the model can only be found in this range of angles by find_ncc_model. The parameter AngleStep determines the step length within the selected range of angles. Hence, if subpixel accuracy is not specified in find_ncc_model, this parameter specifies the accuracy that is achievable for the angles in find_ncc_model. AngleStep should be chosen based on the size of the object. Smaller models do not possess many different discrete rotations in the image, and hence AngleStep should be chosen larger for smaller models. If AngleExtent is not an integer multiple of AngleStep, AngleStep is modified accordingly. To ensure a sampling of the range of possible rotations that is independent of the given AngleStart, the range of possible rotations is modified as follows: If there is no positive integer value n such that AngleStart plus n times AngleStep is exactly 0.0, AngleStart is decreased by up to AngleStep and AngleExtent is increased by AngleStep.
The model is pre-generated for the selected angle range and stored in memory. The memory required to store the model is proportional to the number of angle steps and the number of points in the model. Hence, if AngleStep is too small or AngleExtent too big, it may happen that the model no longer fits into the (virtual) memory. In this case, either AngleStep must be enlarged or AngleExtent must be reduced. In any case, it is desirable that the model completely fits into the main memory, because this avoids paging by the operating system, and hence the time to find the object will be much smaller. Since angles can be determined with subpixel resolution by find_ncc_model, AngleStep >= 1 can be selected for models of a diameter smaller than about 200 pixels. If AngleStep = 'auto' or 0 is selected, create_ncc_model automatically determines a suitable angle step length based on the size of the model. The automatically computed angle step length can be queried using get_ncc_model_params.
The parameter Metric determines the conditions under which the model is recognized in the image. If Metric = 'use_polarity', the object in the image and the model must have the same contrast. If, for example, the model is a bright object on a dark background, the object is found only if it is also brighter than the background. If Metric = 'ignore_global_polarity', the object is found in the image also if the contrast reverses globally. In the above example, the object hence is also found if it is darker than the background. The runtime of find_ncc_model will increase slightly in this case.
The center of gravity of the domain (region) of the model image Template is used as the origin (reference point) of the model. A different origin can be set with set_ncc_model_origin.
This operator returns a handle. Note that the state of an instance of this handle type may be changed by specific operators even though the handle is used as an input parameter by those operators.
Input image whose domain will be used to create the model.
Maximum number of pyramid levels.
Default value: 'auto'
List of values: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 'auto'
Smallest rotation of the pattern.
Default value: -0.39
Suggested values: -3.14, -1.57, -0.79, -0.39, -0.20, 0.0
Extent of the rotation angles.
Default value: 0.79
Suggested values: 6.29, 3.14, 1.57, 0.79, 0.39
Restriction: AngleExtent >= 0
Step length of the angles (resolution).
Default value: 'auto'
Suggested values: 'auto', 0.0, 0.0175, 0.0349, 0.0524, 0.0698, 0.0873
Restriction: AngleStep >= 0 && AngleStep <= pi / 16
Default value: 'use_polarity'
List of values: 'ignore_global_polarity', 'use_polarity'
Handle of the model.
If the parameters are valid, the operator create_ncc_model returns the value 2 (H_MSG_TRUE). If the parameter NumLevels are chosen such that the model contains too few points, the error 8506 is raised.
draw_region, reduce_domain, threshold
find_ncc_model, get_ncc_model_params, clear_ncc_model, write_ncc_model, set_ncc_model_origin, set_ncc_model_param, find_ncc_models
create_shape_model, create_scaled_shape_model, create_aniso_shape_model