fuzzy_measure_pos🔗
Short description🔗
fuzzy_measure_pos — Extract straight edges perpendicular to a rectangle or an annular arc.
Signature🔗
fuzzy_measure_pos( image Image, measure MeasureHandle, number Sigma, number AmpThresh, number FuzzyThresh, string Transition, out point.y RowEdge, out point.x ColumnEdge, out real Amplitude, out real FuzzyScore, out real Distance )
Description🔗
fuzzy_measure_pos extracts straight edges which lie
perpendicular to the major axis of a rectangle or an annular arc.
In addition to measure_pos it uses fuzzy functions to
evaluate and select the edges.
For an explanation of the concept of 1D measuring see the introduction of chapter 1D Measuring.
The algorithm of fuzzy_measure_pos
works by averaging the gray values in “slices”
perpendicular to the major axis of the rectangle or annular arc
in order to obtain
a one-dimensional edge profile. The sampling is done at subpixel
positions in the image Image at integer row and column
distances (in the coordinate frame of the rectangle) from the center
of the rectangle. Since this involves some calculations which can
be used repeatedly in several measurements, the operator
gen_measure_rectangle2 is used to perform these
calculations only once, thus increasing the speed of
fuzzy_measure_pos significantly. Since there is a trade-off
between accuracy and speed in the subpixel calculations of the gray
values, and thus in the accuracy of the extracted edge positions,
different interpolation schemes can be selected in
gen_measure_rectangle2. (The interpolation only
influences rectangles not aligned with the image axes and annular arcs.)
The measure
object generated with gen_measure_rectangle2 is passed
in MeasureHandle.
After the one-dimensional edge profile has been calculated, subpixel
edge locations are computed by convolving the profile with the
derivatives of a Gaussian smoothing kernel of standard deviation
Sigma. Salient edges can be selected with the parameter
AmpThresh, which constitutes a threshold on the amplitude,
i.e., the absolute value of the first derivative of the edge.
Additionally, it is possible to select only positive edges, i.e.,
edges which constitute a dark-to-light transition in the direction
of the major axis of the rectangle (Transition =
'positive'), only negative edges, i.e., light-to-dark
transitions (Transition = 'negative'), or both
types of edges (Transition = 'all'). Finally, it
is possible to select which edge points are returned.
Having extracted subpixel edge locations,
features of these edges are evaluated by a corresponding fuzzy
function, which can be set by set_fuzzy_measure. Which edges
are selected can be determined with the parameter FuzzyThresh,
which constitutes a threshold on the weight over all fuzzy sets, i.e., the
geometric mean of the weights of the defined sets.
The selected edges are returned as single points, which lie on the
major axis of the rectangle or annular arc, in
(RowEdge, ColumnEdge). The corresponding edge
amplitudes are returned in Amplitude, the fuzzy scores in
FuzzyScore. In addition, the
distance between consecutive edge points is returned in
Distance. Here, Distance[i] corresponds to the distance
between Edge[i] and Edge[i+1], i.e., the tuple Distance
contains one element less than the tuples RowEdge and
ColumnEdge.
Attention🔗
fuzzy_measure_pos only returns meaningful results if the
assumptions that the edges are straight and perpendicular to the
major axis of the rectangle are fulfilled. Thus, it should not be
used to extract edges from curved objects, for example.
Furthermore, the user should ensure that the rectangle is as close
to perpendicular as possible to the edges in the image. Additionally,
Sigma must not become larger than approx. 0.5 * Length1
(for Length1 see gen_measure_rectangle2).
It should be kept in mind that fuzzy_measure_pos ignores the
domain of Image for efficiency reasons. If certain regions
in the image should be excluded from the measurement a new measure
object with appropriately modified parameters should be generated.
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.
Parameters🔗
Image (input_object) singlechannelimage → object (byte / uint2 / real)
Input image.
MeasureHandle (input_control) measure → (handle)
Measure object handle.
Sigma (input_control) number → (real)
Sigma of Gaussian smoothing.
Default: 1.0
Suggested values: 0.4, 0.6, 0.8, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0
Value range: 0.4 ≤ Sigma ≤ 100 (lin)
Minimum increment: 0.01
Recommended increment: 0.1
AmpThresh (input_control) number → (real)
Minimum edge amplitude.
Default: 30.0
Suggested values: 5.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 90.0, 110.0
Value range: 1 ≤ AmpThresh ≤ 255 (lin)
Minimum increment: 0.5
Recommended increment: 2
FuzzyThresh (input_control) number → (real)
Minimum fuzzy value.
Default: 0.5
Suggested values: 0.1, 0.3, 0.5, 0.6, 0.7, 0.9
Value range: 0.0 ≤ FuzzyThresh ≤ 1.0 (lin)
Recommended increment: 0.1
Transition (input_control) string → (string)
Select light/dark or dark/light edges.
Default: 'all'
List of values: 'all', 'negative', 'positive'
RowEdge (output_control) point.y-array → (real)
Row coordinate of the edge point.
ColumnEdge (output_control) point.x-array → (real)
Column coordinate of the edge point.
Amplitude (output_control) real-array → (real)
Edge amplitude of the edge (with sign).
FuzzyScore (output_control) real-array → (real)
Fuzzy evaluation of the edges.
Distance (output_control) real-array → (real)
Distance between consecutive edges.
Result🔗
If the parameter values are correct the operator
fuzzy_measure_pos returns the value 2 (H_MSG_TRUE). Otherwise an
exception is raised.
Combinations with other operators🔗
Combinations
Possible predecessors
gen_measure_rectangle2, gen_measure_arc, set_fuzzy_measure
Possible successors
Alternatives
See also
Module🔗
1D Metrology