create_aniso_shape_model_xld🔗
Short description🔗
create_aniso_shape_model_xld — Prepare an anisotropically scaled shape model for matching
from XLD contours.
Signature🔗
create_aniso_shape_model_xld( xld_cont Contours, integer NumLevels, angle.rad AngleStart, angle.rad AngleExtent, angle.rad AngleStep, number ScaleRMin, number ScaleRMax, number ScaleRStep, number ScaleCMin, number ScaleCMax, number ScaleCStep, string Optimization, string Metric, number MinContrast, out shape_model ModelID )
Description🔗
The operator create_aniso_shape_model_xld creates an anisotropically
scaled shape model used for matching from the XLD contours passed in
Contours. The XLD contours represent the gray value edges of the
object to be searched for. In contrast to the operator
create_aniso_shape_model, which creates a shape model from a
template image, the operator create_aniso_shape_model_xld creates
the shape model from XLD contours, i.e., without the use of a template
image.
The output parameter ModelID is a handle for this model, which is
used in subsequent calls to find_aniso_shape_model. The center of
gravity of the smallest surrounding rectangle of the Contours that
is parallel to the coordinate axes is used as the origin (reference point)
of the model. A different origin can be set with
set_shape_model_origin. The model is generated for multiple image
pyramid levels and is stored in memory. If a complete pregeneration of the
model is selected (see below), the model is generated at multiple rotations
and anisotropic scales (i.e., independent scales in the row and
column direction) on each level. The model can be extended by clutter
parameters with set_shape_model_clutter.
Input parameters in detail🔗
-
NumLevels: The number of pyramid levels is determined with the parameterNumLevels. 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,NumLevelsmust be chosen such that the model is still recognizable and contains a sufficient number of points (at least four) on the highest pyramid level. 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_aniso_shape_model_xldreturns with an error message.If
NumLevelsis set to 'auto',create_aniso_shape_model_xlddetermines the number of pyramid levels automatically. The computed number of pyramid levels can be queried usingget_shape_model_params. In rare cases, it might happen thatcreate_aniso_shape_model_xlddetermines 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 forMinScoreorGreedinessinfind_aniso_shape_modelin order to find the model. If the number of pyramid levels is chosen too small, the time required to find the model infind_aniso_shape_modelmay increase. In these cases, the number of pyramid levels should be selected manually. -
AngleStart,AngleExtent, andAngleStep: The parametersAngleStartandAngleExtentdetermine the range of possible rotations, in which the object can occur in the image. Note that the object can only be found in this range of angles byfind_aniso_shape_model. The parameterAngleStepdetermines the step length within the selected range of angles. Hence, if subpixel accuracy is not specified infind_aniso_shape_model, this parameter specifies the accuracy that is achievable for the angles infind_aniso_shape_model.AngleStepshould be chosen based on the size of the object. Smaller models do not have many different discrete rotations in the image, and henceAngleStepshould be chosen larger for smaller models. IfAngleExtentis not an integer multiple ofAngleStep,AngleStepis modified accordingly. To ensure that for model instances without rotation angle values of exactly 0.0 are returned byfind_aniso_shape_model, the range of possible rotations is modified as follows: If there is no positive integer value n such thatAngleStartplus n timesAngleStepis exactly 0.0,AngleStartis decreased by up toAngleStepandAngleExtentis increased byAngleStep. -
ScaleRMin,ScaleRMax,ScaleCMin,ScaleCMax,ScaleRStep, andScaleCStep: The parametersScaleRMin,ScaleRMax,ScaleCMin, andScaleCMaxdetermine the range of possible anisotropic scales of the object in the row and column direction. A scale of 1 in both scale factors corresponds to the original size of the model. The parametersScaleRStepandScaleCStepdetermine the step length within the selected range of scales. Hence, if subpixel accuracy is not specified infind_aniso_shape_model, these parameters specify the accuracy that is achievable for the scales infind_aniso_shape_model. LikeAngleStep,ScaleRStepandScaleCStepshould be chosen based on the size of the object. If the respective range of scales is not an integer multiple ofScaleRStepandScaleCStep,ScaleRStepandScaleCStepare modified accordingly.To ensure that for model instances that are not scaled scale values of exactly 1.0 are returned by
find_aniso_shape_model, the range of possible scales is modified as follows: If there are no positive integer values n and m such thatScaleRMinplus n timesScaleRStepis exactly 1.0 andScaleCMinplus m timesScaleCStepis exactly 1.0,ScaleRMinandScaleCMinare decreased by up toScaleRStepandScaleCStep, respectively, andScaleRMaxandScaleCMaxare increased such that the range of possible scales is increased byScaleRStepandScaleCStep, respectively.Note that the transformations are treated internally such that the scalings are applied first, followed by the rotation. Therefore, the model should usually be aligned such that it appears horizontally or vertically in the model image.
-
Optimization: For particularly large models, it may be useful to reduce the number of model points by settingOptimizationto a value different from 'none'. IfOptimization\(=\) 'none', all model points are stored. In all other cases, the number of points is reduced according to the value ofOptimization. If the number of points is reduced, it may be necessary infind_aniso_shape_modelto set the parameterGreedinessto a smaller value, e.g., 0.7 or 0.8. For small models, the reduction of the number of model points does not result in a speed-up of the search because in this case usually significantly more potential instances of the model must be examined.If
Optimizationis set to 'auto',create_aniso_shape_model_xldautomatically determines the reduction of the number of model points. -
Metric: The parameterMetricdetermines 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 offind_aniso_shape_modelwill increase slightly in this case.Note that the metrics ('use_polarity' and 'ignore_global_polarity') can only be selected if all
Contoursprovide the attribute 'edge_direction', which defines the polarity of the edges. This attribute is available for contours created, e.g., withedges_sub_pixwith the parameterMethodset to, e.g., 'canny'. Otherwise, these two metrics can be selected with the operatorset_shape_model_metric, which determines the polarity of the edges from an image.If
Metric\(=\) 'ignore_local_polarity', the model is found even if the contrast changes locally. This mode can, for example, be useful if the object consists of a part with medium gray value, within which either darker or brighter sub-objects lie. Since in this case the runtime offind_aniso_shape_modelincreases significantly, it is usually better to create several models that reflect the possible contrast variations of the object withcreate_aniso_shape_model_xld, and to match them simultaneously withfind_aniso_shape_models.The above three metrics can only be applied to single-channel images. If a multichannel image is used as the model image or as the search image, only the first channel will be used (and no error message will be returned).
If
Metric\(=\) 'ignore_color_polarity', the model is found even if the color contrast changes locally. This is, for example, the case if parts of the object can change their color, e.g., from red to green. In particular, this mode is useful if it is not known in advance in which channels the object is visible. In this mode, the runtime offind_aniso_shape_modelcan also increase significantly. The metric 'ignore_color_polarity' can be used for images with an arbitrary number of channels. If it is used for single-channel images it has the same effect as 'ignore_local_polarity'. It should be noted that forMetric\(=\) 'ignore_color_polarity' the channels do not need to contain a spectral subdivision of the light (like in an RGB image). The channels can, for example, also contain images of the same object that were obtained by illuminating the object from different directions.Note that the first two metrics ('use_polarity' and 'ignore_global_polarity') can only be selected if all
Contoursprovide the attribute 'edge_direction', which defines the polarity of the edges. For more information about contour attributes like 'edge_direction' seeget_contour_attrib_xld. Otherwise, these two metrics can be selected with the operatorset_shape_model_metric, which determines the polarity of the edges from an image. -
MinContrast: WithMinContrast, it can be determined which contrast the object edges must at least have in the recognition performed byfind_aniso_shape_model. In other words, this parameter separates the object from the noise in the image. Therefore, a good choice is the range of gray value changes caused by the noise in the image. If, for example, the gray values fluctuate within a range of 10 gray levels,MinContrastshould be set to 10. If multichannel images are used for the model and the search images, and if the parameterMetricis set to 'ignore_color_polarity' (see above) the noise in one channel must be multiplied by the square root of the number of channels to determineMinContrast. If, for example, the gray values fluctuate within a range of 10 gray levels in a single channel and the image is a three-channel imageMinContrastshould be set to 17. If the model should be recognized in very low contrast images,MinContrastmust be set to a correspondingly small value. If the model should be recognized even if it is severely occluded,MinContrastshould be slightly larger than the range of gray value fluctuations created by noise in order to ensure that the position and rotation of the model are extracted robustly and accurately byfind_aniso_shape_model.
Complete pregeneration of the model🔗
Optionally, a second value can be passed in Optimization.
This value determines whether the model is pregenerated completely
or not. To do so, the second value of Optimization must be
set to either 'pregeneration' or
'no_pregeneration'. If the second value is not used (i.e.,
if only one value is passed), the mode that is set with
set_system('pregenerate_shape_models',...) is used. With
the default value ('pregenerate_shape_models' \(=\)
'false'), the model is not pregenerated completely. The
complete pregeneration of the model normally leads to slightly lower
runtimes because the model does not need to be transformed at
runtime. However, in this case, the memory requirements and the
time required to create the model are significantly higher. It
should also be noted that it cannot be expected that the two modes
return exactly identical results because transforming the model at
runtime necessarily leads to different internal data for the
transformed models than pregenerating the transformed models. For
example, if the model is not pregenerated completely,
find_aniso_shape_model typically returns slightly lower
scores, which may require setting a slightly lower value for
MinScore than for a completely pregenerated model.
Furthermore, the poses obtained by interpolation may differ slightly
in the two modes.
If maximum accuracy is desired, the pose of the model should
be determined by least-squares adjustment.
If a complete pregeneration of the model is selected,
the model is pregenerated for the selected angle and scale range
and stored in memory. The memory required to store the model is
proportional to the number of angle steps, the number of scale
steps, and the number of points in the model. Hence, if
AngleStep, ScaleRStep, or ScaleCStep are
too small or AngleExtent or the range of scales are too
big, it may happen that the model no longer fits into the (virtual)
memory. In this case, AngleStep, ScaleRStep, or
ScaleCStep must be enlarged or AngleExtent or the
range of scales 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_aniso_shape_model,
AngleStep >= 1° and
ScaleRStep, ScaleCStep >= 0.02 can be
selected for models of a diameter smaller than about 200 pixels.
If AngleStep =
‘auto’ or ScaleRStep, ScaleCStep =
‘auto’
is selected, create_aniso_shape_model_xld automatically
determines a suitable angle or scale step length, respectively,
based on the size of the model. The automatically computed angle
and scale step lengths can be queried using
get_shape_model_params.
If a complete pregeneration of the model is not selected, the model
is only created in a reference pose on each pyramid level. In this
case, the model must be transformed to the different angles and
scales at runtime in find_aniso_shape_model. Because of
this, the recognition of the model might require slightly more time.
Note that pregenerated shape models are tailored to a specific image size. For runtime reasons using images of different sizes during the search with the same model in parallel is not supported. In this case, copies of the same model must be used, otherwise the program may crash!
Attention🔗
The XLD contours passed in Contours should have been scaled
to approximately the average size of the object in the search images.
This means that the products \(\textrm{ScaleRMin} \times \textrm{ScaleRMax}\) and
\(\textrm{ScaleCMin} \times \textrm{ScaleCMax}\) should be
approximately equal to 1.
Note that, in contrast to the operator
create_aniso_shape_model, it is not possible to specify a
minimum size of the model components. To avoid small model
components in the shape model, short contours can be eliminated
before calling create_aniso_shape_model_xld with the
operator select_contours_xld.
Execution information🔗
Execution information
-
Multithreading type: reentrant (runs in parallel with non-exclusive operators).
-
Multithreading scope: global (may be called from any thread).
-
Processed without parallelization.
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.
Parameters🔗
Contours (input_object) xld_cont(-array) → object
Input contours that will be used to create the model.
NumLevels (input_control) integer → (integer / string)
Maximum number of pyramid levels.
Default: 'auto'
List of values: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 'auto'
AngleStart (input_control) angle.rad → (real)
Smallest rotation of the pattern.
Default: -0.39
Suggested values: -3.14, -1.57, -0.79, -0.39, -0.20, 0.0
AngleExtent (input_control) angle.rad → (real)
Extent of the rotation angles.
Default: 0.79
Suggested values: 6.29, 3.14, 1.57, 0.79, 0.39
Restriction: AngleExtent >= 0
AngleStep (input_control) angle.rad → (real / string)
Step length of the angles (resolution).
Default: 'auto'
Suggested values: 'auto', 0.0175, 0.0349, 0.0524, 0.0698, 0.0873
Restriction: AngleStep >= 0 && AngleStep <= pi/2
ScaleRMin (input_control) number → (real)
Minimum scale of the pattern in the row direction.
Default: 0.9
Suggested values: 0.5, 0.6, 0.7, 0.8, 0.9, 1.0
Restriction: ScaleRMin > 0
ScaleRMax (input_control) number → (real)
Maximum scale of the pattern in the row direction.
Default: 1.1
Suggested values: 1.0, 1.1, 1.2, 1.3, 1.4, 1.5
Restriction: ScaleRMax >= ScaleRMin
ScaleRStep (input_control) number → (real / string)
Scale step length (resolution) in the row direction.
Default: 'auto'
Suggested values: 'auto', 0.01, 0.02, 0.05, 0.1, 0.15, 0.2
Restriction: ScaleRStep >= 0
ScaleCMin (input_control) number → (real)
Minimum scale of the pattern in the column direction.
Default: 0.9
Suggested values: 0.5, 0.6, 0.7, 0.8, 0.9, 1.0
Restriction: ScaleCMin > 0
ScaleCMax (input_control) number → (real)
Maximum scale of the pattern in the column direction.
Default: 1.1
Suggested values: 1.0, 1.1, 1.2, 1.3, 1.4, 1.5
Restriction: ScaleCMax >= ScaleCMin
ScaleCStep (input_control) number → (real / string)
Scale step length (resolution) in the column direction.
Default: 'auto'
Suggested values: 'auto', 0.01, 0.02, 0.05, 0.1, 0.15, 0.2
Restriction: ScaleCStep >= 0
Optimization (input_control) string(-array) → (string)
Kind of optimization and optionally method used for generating the model.
Default: 'auto'
List of values: 'auto', 'no_pregeneration', 'none', 'point_reduction_high', 'point_reduction_low', 'point_reduction_medium', 'pregeneration'
Metric (input_control) string → (string)
Match metric.
Default: 'ignore_local_polarity'
List of values: 'ignore_color_polarity', 'ignore_global_polarity', 'ignore_local_polarity', 'use_polarity'
MinContrast (input_control) number → (integer)
Minimum contrast of the objects in the search images.
Default: 5
Suggested values: 1, 2, 3, 5, 7, 10, 20, 30, 40
ModelID (output_control) shape_model → (handle)
Handle of the model.
Result🔗
If the parameters are valid, the operator
create_aniso_shape_model_xld returns the value 2 (H_MSG_TRUE). If necessary an
exception is raised. If the parameter NumLevels is chosen such that
the model contains too few points, the error 8510 is raised.
Combinations with other operators🔗
Combinations
Possible predecessors
read_contour_xld_dxf, edges_sub_pix, select_contours_xld
Possible successors
find_aniso_shape_model, find_aniso_shape_models, get_shape_model_params, clear_shape_model, write_shape_model, set_shape_model_origin, set_shape_model_param, set_shape_model_metric, set_shape_model_clutter
Alternatives
See also
Module🔗
Matching