This chapter contains operators for 1D measuring.
With 1D measuring, edges, i.e., transitions from light to dark or from dark to light, can be located along a predefined line or arc. This allows you to measure the dimension of parts fast and easily with high accuracy. Note that if you want to measure the dimensions of geometric primitives like circles, ellipses, rectangles, or lines, and approximate values for the positions, orientations, and geometric shapes are known, 2D Metrology may be a suitable alternative.
(1) | (2) |
In the following, the steps that are required to use 1D measuring are described briefly.
First, a measure object must be generated that describes the region of interest for the measurement. If the measurement should be performed along a line, the measure object is defined by a rectangle. If it should be performed along an arc, the measure object is defined as an annual arc. The measure objects are generated by the operators
Note that you can use shape-based matching (see chapter Matching / Shape-Based) to automatically align the measure objects.
Then, the actual measurement is performed. For this, typically one of the following operators is used:
extracts straight edges perpendicular to the main
axis of the measure object and returns the positions of the edge centers, the
edge amplitudes, and the distances between consecutive edges.
measure_pos
extracts straight edge pairs perpendicular to the
main axis of the measure object and returns the positions of the edge centers
of the edge pairs, the edge amplitudes for the edge pairs, the distances
between the edges of an edge pair, and the distances between consecutive edge
pairs.
measure_pairs
extracts points with a particular gray value
along the main axis of the measure object and returns their positions and the
distances between consecutive points.
measure_thresh
Alternatively, if there are extra edges that do not belong to the
measurement, fuzzy measuring can be applied. Here, so-called fuzzy rules,
which describe the features of good edges, must be defined. Possible features
are, e.g., the position, the distance, the gray values, or the amplitude of
edges. These functions are created with
and
passed to the tool with create_funct_1d_pairs
or
set_fuzzy_measure
. Then, based on these rules, one of the
following operators will extract the most appropriate edges:
set_fuzzy_measure_norm_pair
extracts straight edges perpendicular to the
main axis of the measure object and returns the positions of the edge
centers, the edge amplitudes, the fuzzy scores, and the distances between
consecutive edges.
fuzzy_measure_pos
extracts straight edge pairs perpendicular
to the main axis of the measure object and returns the positions of the first
and second edges of the edge pairs, the edge amplitudes for the edge pairs,
the positions of the centers of the edge pairs, the fuzzy scores, the
distances between the edges of an edge pair, and the distances between
consecutive edge pairs.
fuzzy_measure_pairs
is similar to fuzzy_measure_pairing
with the exception that it is also possible to extract interleaving and
included pairs using the parameter Pairing.
fuzzy_measure_pairs
Alternatively to the automatical extraction of edges or points within the measure object, you can also extract a one-dimensional gray value profile perpendicular to the rectangle or annular arc and evaluate this gray value information according to your needs. The gray value profile within the measure object can be extracted with the operator
When you no longer need the measure object, you destroy it by passing the handle to
In addition to the operators mentioned above, you can use
to discard a fuzzy function of a fuzzy set that
was set via reset_fuzzy_measure
or set_fuzzy_measure
before, set_fuzzy_measure_norm_pair
to translate the reference point of the
measure object to a specified position, translate_measure
and
write_measure
to write the measure object to file and read it from
file again, and read_measure
and serialize_measure
to
serialize and deserialize the measure object.
deserialize_measure
In the following, the most important terms that are used in the context of 1D Measuring are described.
A data structure that contains a specific region of interest that is prepared for the extraction of straight edges which lie perpendicular to the major axis of a rectangle or an annular arc.
A circular arc with an associated width.
See also the “Solution Guide Basics”
and
“Solution Guide on 1D Measuring”
for further details about
1D Measuring.
close_measure
deserialize_measure
fuzzy_measure_pairing
fuzzy_measure_pairs
fuzzy_measure_pos
gen_measure_arc
gen_measure_rectangle2
measure_pairs
measure_pos
measure_projection
measure_thresh
read_measure
reset_fuzzy_measure
serialize_measure
set_fuzzy_measure
set_fuzzy_measure_norm_pair
translate_measure
write_measure