National Instruments IMAQ Vision for LabWindows TM /CVI - Manual (Page 93)

Chapter 6 Calibrating Images
IMAQ Vision for LabWindows/CVI User Manual 6-8 ni.com
If the learning process returns a learning score below 600, try the following:
1. Make sure your grid complies with the guidelines listed in the
Defining a Calibration Template section of this chapter.
2. Check the lighting conditions. If you have too much or too little
lighting, the software may estimate the center of the dots incorrectly.
Also, adjust the range parameter to distinguish the dots from the
background.
3. Select another learning algorithm. When nonlinear lens distortion is
present, using perspective projection sometimes results in a low
learning score.
Learning the Error Map
An error map helps you gauge the quality of your complete system.
The error map returns an estimated error range to expect when a pixel
coordinate is transformed into a real-world coordinate. The transformation
accuracy may be higher than the value the error range indicates. Set the
learnMap element of the options parameter to TRUE to learn the error
map.
Learning the Correction Table
If the speed of image correction is a critical factor for your application, use
a correction table. The correction table is a lookup table stored in memory
that contains the real-world location information of all the pixels in the
image. The extra memory requirements for this option are based on the size
of the image. Use this option when you want to correct several images at a
time in your vision application. Set the
learnTable element of the
options parameter to TRUE to learn the correction table.
Setting the Scaling Method
Use the method element of the options parameter to choose the appearance
of the corrected image. Select either IMAQ_SCALE_TO_FIT or
IMAQ_SCALE_TO_PRESERVE_AREA . Refer to Chapter 3, System Setup and
Calibration, of the IMAQ Vision Concepts Manual for more information
about the scaling methods.
Calibration Invalidation
Any image processing operation that changes the image size or orientation
voids the calibration information in a calibrated image. Examples of
functions that void calibration information include
imaqResample() ,
imaqScale() , imaqArrayToImage() , and imaqUnwrap() .