National Instruments IMAQ Vision for Measurement Studio User Manual Page 63
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Chapter 5 Machine Vision
© National Instruments Corporation 5-17 IMAQ Vision for LabWindows/CVI User Manual
However, there may be applications in which the assumptions used in the
algorithm are not optimal. Knowing your particular application and the
images you want to process is useful in selecting the pattern matching
parameters. The following are parameters the influence the IMAQ Vision
pattern matching algorithm.
Match Mode
You can set the match mode to control how the pattern matching algorithm
treats the template at different orientations. If you expect the orientation of
valid matches to vary less than ±5° from the template, set the
mode
element
of the options parameter to
IMAQ_MATCH_SHIFT_INVARIANT
.Otherwise,
set the mode element to
IMAQ_MATCH_ROTATION_INVARIANT
.
Shift-invariant matching is faster than rotation-invariant matching.
Minimum Contrast
You can set the minimum contrast to potentially increase the pattern
matching algorithm’s speed. Contrast is the difference between the smallest
and largest pixel values in a region. The pattern matching algorithm ignores
all image regions where contrast values fall beneath a set minimum contrast
value. If the search image has high contrast but contains some low contrast
regions, you can set a high minimum contrast value. By using a high
minimum contrast value, you exclude all areas in the image with low
contrast, significantly reducing the region in which the pattern matching
algorithm must search. If the search image has low contrast throughout, set
a low minimum contrast parameter to ensure that the pattern matching
algorithm looks for the template in all regions of the image. Use the
minContrast
element of the
imaqMatchPattern()
options parameter
to set the minimum contrast.
Rotation Angle Ranges
For matching objects that may rotate in the image, the pattern matching
algorithm, by default, allows any orientation between 0° to 360°.Ifthe
pattern rotation in your application is restricted to a certain range (for
example, from –15° to 15°), you can provide this information to the pattern
matching algorithm by setting the
angleRanges
element of the
imaqMatchPattern()
options parameter. This information improves
your search time because the pattern matching algorithm looks for the
pattern at fewer angles.
- IMAQ Vision 1
- User Manual 1
- Important Information 3
- Conventions 4
- Contents 5
- Chapter 4 6
- Chapter 5 6
- Introduction to IMAQ Vision 8
- IMAQ Vision Function Tree 9
- Table 1-1 10
- IMAQ Vision Function Types 10
- NIMachineVision.fp 11
- Getting Measurement-Ready 14
- Calibrate Your Imaging System 15
- Create an Image 15
- Source and Destination Images 17
- AcquireorReadanImage 18
- Acquiring an Image 19
- Reading a File 19
- Display an Image 20
- Analyze an Image 21
- Improve an Image 22
- Convolution Filter 23
- Nth Order Filter 24
- Grayscale Morphology 24
- Complex Image Operations 26
- Grayscale and Color 27
- Measurements 27
- Figure 3-2. ROI Constructor 30
- Defining Regions with Masks 32
- Measure Grayscale Statistics 33
- Measure Color Statistics 33
- Comparing Colors 34
- Learning Color Information 35
- Using the Entire Image 36
- Using a Region in the Image 36
- Ignoring Learned Colors 39
- Blob Analysis 40
- Correct Image Distortion 41
- Create a Binary Image 41
- Improve the Binary Image 42
- Make Particle Measurements 43
- Chapter 4 Blob Analysis 44
- Machine Vision 47
- Locate Objects to Inspect 48
- Chapter 5 Machine Vision 49
- Figure 5-3 51
- IMAQ_MATCH_ROTATION_INVARIANT 52
- IMAQ_MATCH_SHIFT_INVARIANT 52
- IMAQ_FIND_REFERENCE 52
- IMAQ_UPDATE_TRANSFORM 52
- Set Search Areas 54
- Find Measurement Points 55
- Symmetry 59
- Feature detail 60
- Positional information 60
- Defining a Search Area 61
- Match Mode 63
- Minimum Contrast 63
- Rotation Angle Ranges 63
- Color Information 65
- Feature Detail 66
- Positional Information 66
- Background Information 66
- Color Sensitivity 69
- Search Strategy 69
- Color Score Weight 70
- Make Measurements 72
- Display Results 74
- Calibration 76
- CoordinateSystem 77
- Chapter 6 Calibration 78
- Specifying Scaling Factors 81
- Choosing a Region of Interest 81
- Choosing a Learning Algorithm 81
- Using the Learning Score 82
- Learning the Error Map 83
- Learning the Correction Table 83
- Setting the Scaling Method 83
- Calibration Invalidation 83
- Simple Calibration 84
- Save Calibration Information 85
- Technical Support Resources 86
- Worldwide Support 87
- Glossary 100
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