Document Outline

• IMAQ Vision for Measurement Studio™ User Manual
• Support
  • Worldwide Technical Support and Product Information
  • National Instruments Corporate Headquarters
  • Worldwide Offices
• Important Information
  • Warranty
  • Copyright
  • Trademarks
  • WARNING REGARDING USE OF NATIONAL INSTRUMENTS PRODUCTS
• Conventions
• Contents
• Chapter 1 Introduction to IMAQ Vision
  • About IMAQ Vision
  • Documentation and Examples
  • Application Development Environments
  • IMAQ Vision Function Tree
    • Table 1-1. IMAQ Vision Function Types
  • IMAQ Machine Vision Function Tree
    • Table 1-2. IMAQ Machine Vision Function Types
  • Creating IMAQ Vision Applications
    • Figure 1-1. General Steps to Designing a Vision Application
    • Figure 1-2. Inspection Steps for Building a Vision Application
• Chapter 2 Getting Measurement-Ready Images
  • Set Up Your Imaging System
  • Calibrate Your Imaging System
  • Create an Image
    • Table 2-1. IMAQ Vision for LabWindows/CVI Image Types
    • Source and Destination Images
  • Acquire or Read an Image
    • Acquiring an Image
    • Reading a File
    • Converting an Array to an Image
  • Display an Image
  • Attach Calibration Information
  • Analyze an Image
  • Improve an Image
    • Lookup Tables
    • Filters
      • Convolution Filter
      • Nth Order Filter
    • Grayscale Morphology
    • FFT
      • Complex Image Operations
• Chapter 3 Grayscale and Color Measurements
  • Figure 3-1. Steps to Taking Grayscale and Color Measurements
  • Define Regions of Interest
    • Interactively Defining Regions
      • Table 3-1. Tools Palette Functions
      • Figure 3-2. ROI Constructor
      • Figure 3-3. Tools Palette Tools and Information
    • Programmatically Defining Regions
    • Defining Regions with Masks
  • Measure Grayscale Statistics
  • Measure Color Statistics
    • Figure 3-4. Primary Components of a Color Image
    • Comparing Colors
    • Learning Color Information
      • Choosing the Right Color Information
      • Figure 3-5. Template Color Information
      • Specifying the Color Information to Learn
      • Figure 3-6. Using the Entire Image to Learn Color Distribution
      • Figure 3-7. Using a Single Region to Learn Color Distribution
      • Figure 3-8. Using Multiple Regions to Learn Color Distribution
      • Choosing a Color Representation Sensitivity
      • Ignoring Learned Colors
• Chapter 4 Blob Analysis
  • Figure 4-1. Steps to Performing Blob Analysis
  • Correct Image Distortion
  • Create a Binary Image
  • Improve the Binary Image
    • Removing Unwanted Blobs
    • Separating Touching Blobs
    • Improving Blob Shapes
  • Make Particle Measurements
    • Table 4-1. Particle Measurements
  • Convert Pixel Coordinates to Real-World Coordinates
• Chapter 5 Machine Vision
  • Figure 5-1. Steps to Performing Machine Vision
  • Locate Objects to Inspect
    • Using Edge Detection to Build a Coordinate Transform
      • Figure 5-2. Coordinate Systems of a Reference Image and Inspection Image
      • Figure 5-3. Locating Coordinate System Axes with Two Search Areas
    • Using Pattern Matching to Build a Coordinate Transform
    • Choosing a Method to Build the Coordinate Transform
      • Figure 5-4. Building a Coordinate Transform
  • Set Search Areas
    • Interactively Defining Regions
    • Programmatically Defining Regions
  • Find Measurement Points
    • Finding Features Using Edge Detection
      • Finding Lines or Circles
      • Figure 5-5. Finding a Straight Feature
      • Figure 5-6. Finding a Circular Feature
      • Finding Edge Points Along One Search Contour
      • Finding Edge Points Along Multiple Search Contours
    • Finding Points Using Pattern Matching
      • Defining and Create Good Template Images
      • Figure 5-7. Symmetry
      • Figure 5-8. Feature Detail
      • Figure 5-9. Positional Information
      • Figure 5-10. Background Information
      • Training the Pattern Matching Algorithm
      • Defining a Search Area
      • Figure 5-11. Selecting a Search Area for Grayscale Pattern Matching
      • Setting Matching Parameters and Tolerances
      • Testing the Search Algorithm on Test Images
      • Using a Ranking Method to Verify Results
    • Finding Points Using Color Pattern Matching
      • Defining and Creating Good Color Template Images
      • Training the Color Pattern Matching Algorithm
      • Defining a Search Area
      • Figure 5-12. Selecting a Search Area for Color Pattern Matching
      • Setting Matching Parameters and Tolerances
      • Testing the Search Algorithm on Test Images
    • Finding Points Using Color Location
  • Convert Pixel Coordinates to Real-World Coordinates
  • Make Measurements
    • Distance Measurements
    • Analytic Geometry Measurements
    • Instrument Reader Measurements
  • Display Results
• Chapter 6 Calibration
  • Perspective and Nonlinear Distortion Calibration
    • DefiningaCalibration Template
      • Figure 6-1. Defining a Calibration Grid
    • Defininga Reference Coordinate System
      • Figure 6-2. Axis Direction in the Image Plane
      • Figure 6-3. A Calibration Grid and an Image of the Grid
      • Figure 6-4. Defining a Coordinate System
    • Learning Calibration Information
      • Specifying Scaling Factors
      • Choosing a Region of Interest
      • Choosing a Learning Algorithm
      • Figure 6-5. Types of Image Distortion
      • Figure 6-6. Calibration ROIs
      • Using the Learning Score
      • Learning the Error Map
      • Learning the Correction Table
      • Setting the Scaling Method
      • Calibration Invalidation
  • Simple Calibration
    • Figure 6-7. Defining a Simple Calibration
  • Save Calibration Information
  • Attach Calibration Information
• Appendix A Technical Support Resources
• Glossary
  • Numbers/Symbols
  • A
  • B
  • C
  • D
  • E-F
  • G
  • H
  • I
  • J-L
  • M
  • N
  • O-P
  • Q-R
  • S
  • T
  • V-W
• Index
  • A-C
  • D-F
  • G-I
  • L-M
  • N-R
  • S-Z