National Instruments IMAQ Vision for Measurement Studio User Manual Page 72
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Chapter 5 Machine Vision
IMAQ Vision for LabWindows/CVI User Manual 5-26 ni.com
Convert Pixel Coordinates to Real-World Coordinates
The measurement points you located with edge detection and pattern
matching are in pixel coordinates. If you need to make measurements using
real-world units, use
imaqTransformPixelToRealWorld()
to convert
the pixel coordinates into real-world units.
Make Measurements
You can make different types of measurements either directly from the
image or from points that you detect in the image.
Distance Measurements
Use the following functions to make distance measurements for your
inspection application.
Clamp functions measure the separation between two edges in a
rectangular search region. First, clamp functions detect points along the
two edges using the rake function. Then, they compute the distance
between the points detected on the edges along each search line of the rake
and return the largest or smallest distance. The
imaqSelectRect()
function generates a valid input search region for these functions. You also
need to specify the parameters for edge detection and the separation
between the search lines that you want to use within the search region to
find the edges. These functions work directly on the image under
inspection, and they output the coordinates of all the edge points that they
find. The following list describes the available clamp functions:
•
imaqClampMax()
—Measures the largest separation between
two edges in a rectangular search region.
•
imaqClampMin()
—Finds the smallest separation between two edges.
Use
imaqGetDistance()
to compute the distances between two points,
such as consecutive pairs of points in an array of points. You can obtain
these points from the image using any one of the feature detection methods
described in the Find Measurement Points section of this chapter.
- 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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