Instrument reader measurements, Identify parts under inspection, Classifying samples – National Instruments IMAQTM User Manual

Page 80: Instrument reader measurements -28, Identify parts under inspection -28, Classifying samples -28

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Chapter 5

Performing Machine Vision Tasks

IMAQ Vision for Visual Basic User Manual

5-28

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FindMidLine

—Finds the line that is midway between a point and a

line and is parallel to the line.

FindPolygonArea

—Calculates the area of a polygon specified by its

vertex points.

Instrument Reader Measurements

You can make measurements based on the values obtained by meter, LCD,
and barcode readers.

Use

CWIMAQMeterArc.CreateFromPoints

or

CWIMAQMeterArc.CreateFromLines

to calibrate a meter or

gauge that you want to read.

CWIMAQMeterArc.CreateFromLines

calibrates the meter using the initial position and the full-scale position
of the needle.

CWIMAQMeterArc.CreateFromPoints

calibrates the

meter using three points on the meter: the base of the needle, the tip of
the needle at its initial position, and the tip of the needle at its full-scale
position. Use

CWIMAQVision.ReadMeter

to read the position of the

needle using the CWIMAQMeterArc object.

Use

CWIMAQVision.FindLCDSegments

to calculate the regions of

interest around each digit in an LCD or LED. To find the area of each
digit, all the segments of the indicator must be activated. Use

CWIMAQVision.ReadLCD

to read the digits of an LCD or LED.

Identify Parts Under Inspection

In addition to making measurements after you set regions of inspection,
you also can identify parts using classification, OCR, and barcode reading.

Classifying Samples

Use classification to identify an unknown object by comparing a set of its
significant features to a set of features that conceptually represent classes
of known objects. Typical applications involving classification include the
following:

Sorting—Sorts objects of varied shapes. For example, sorting different
mechanical parts on a conveyor belt into different bins.

Inspection—Inspects objects by assigning each object an identification
score and then rejecting objects that do not closely match members of
the training set.

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