National Instruments IMAQ Vision for Measurement Studio User Manual Page 41
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Chapter 4 Blob Analysis
IMAQ Vision for LabWindows/CVI User Manual 4-2 ni.com
Correct Image Distortion
If you need to make accurate shape measurements based on the blobs in
an image containing perspective and nonlinear distortion errors, correct
the distortion using the calibration information you attached to your
image. Use
imaqCorrectCalibratedImage()
to correct distortion in
your grayscale image before thresholding it. See Chapter 6, Calibration,
for more information about correcting an image using calibration
information.
Create a Binary Image
Threshold your grayscale or color image to create a binary image. Creating
a binary image separates the objects that you want to inspect from the
background. The threshold operation sets the background pixels to 0 in the
binary image, while setting the object pixels to a non-zero value. Object
pixels have a value of 1 by default, but you can set the object pixels to any
value or retain their original value.
You can use different techniques to threshold your image. If all the
objects of interest in your grayscale image fall within a continuous range
of intensities and you can specify this threshold range manually, use
imaqThreshold()
to threshold your image.
If all the objects in your grayscale image are either brighter or darker than
your background, you can use
imaqAutoThreshold()
to automatically
determine the optimal threshold range and threshold your image.
Automatic thresholding techniques offer more flexibility than simple
thresholds based on fixed ranges. Because automatic thresholding
techniques determine the threshold level according to the image histogram,
the operation is more independent of changes in the overall brightness and
contrast of the image than a fixed threshold. These techniques are more
resistant to changes in lighting, which makes them well suited for
automated inspection tasks.
If your grayscale image contains objects that have multiple discontinuous
grayscale values, use
imaqMultithreshold()
to specify multiple
threshold ranges.
If you need to threshold a color image, use
imaqColorThreshold()
.
You must specify threshold ranges for each of the color planes (either Red,
Green, and Blue or Hue, Saturation, and Luminance). The binary image
resulting from a color threshold is an 8-bit binary image.
- 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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