create_ncc_model — Prepare an NCC model for matching.
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
The model is generated using multiple image pyramid levels at
multiple rotations on each level and is stored in memory. The
ModelID is a handle for this model, which
is used in subsequent calls to
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,
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
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
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
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
may increase. In these cases, the number of pyramid levels should
be selected by inspecting the output of
Mode = 'constant' and
0.5 should be used.
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
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
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
AngleExtent is increased by
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.
AngleStep is too small or
too big, it may happen that the model no longer fits into the
(virtual) memory. In this case, either
AngleStep must be
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
AngleStep >= 1 can be
selected for models of a diameter smaller than about 200 pixels. If
'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
Metric determines the conditions under which
the model is recognized in the image. If
'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
'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
find_ncc_model will increase slightly in this
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
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.
→object (byte / uint2)
Input image whose domain will be used to create the model.
→(integer / string)
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
AngleExtent >= 0
→(real / string)
Step length of the angles (resolution).
Default value: 'auto'
Suggested values: 'auto', 0.0, 0.0175, 0.0349, 0.0524, 0.0698, 0.0873
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
returns the value 2 (H_MSG_TRUE). If the parameter
chosen such that the model contains too few points, the error 8506