Manuals / Brands / Computer Equipment / Network Card / National Instruments / Computer Equipment / Network Card

National Instruments IMAQ Vision for Measurement Studio Testingthe Search Algorithm on Test Images

1 114

Download 114 pages, 1.93 Mb

Chapter5 MachineVision

IMAQVision for LabWindows/CVI User Manual 5-24 ni.com

Note Use the IMAQ_CONSERVATIVEstr ategyif you have multiple targets located very

close toeach other in the image.

Decide on the best strategyby experimenting with the different options.

Color Score Weight

Whenyou search for a template using both color and shape information, the

colorand shape scores generated during the match process are combined to

generate the final color pattern matching score. The color score weight

determines the contribution of the color score to the final color pattern

matchingscore. If the template’s color in formation is superior to its shape

information, set the weight higher. For example, if you set colorWeight

to 1000, the algorithm finds each match byusing both color and shape

informationand then ranks the matches based entirely on their color scores.

If you set colorWeight to0, the m atches are ranked basedentirely on

their shape scores.

Minimum Contrast

Use the minContrastelement to increase the color pattern matching

algorithm’sspeed . The color pattern matching algorithm ignores all image

regions where grayscalecontrast values fall beneath a set minimum

contrast value. See the Setting Matching Parameters and Tolerances

section of this chapter for more information about minimum contrast.

Rotation Angle Ranges

If you know that the pattern rotation is restricted to a certain range (for

example, between –15° to15°), provid eth is restriction information to

the pattern matching algorithm by setting the angleRanges element. This

informationimproves your search time because the color pattern matching

algorithm looks for the pattern at fewer angles. See Chapter 12, Pattern

Matching,intheIMAQ Vision Concepts Manual for more information on

pattern matching.

Testingthe Search Algorithm on Test Images

To determine if your selected template or reference pattern is appropriate

foryour machine visi ona pplication, test the template on a few test images

by using imaqMatchColorPattern().These test images should reflect

the images generated by yourmachine visionapplication during true

operating conditions. If the pattern matching algorithm locates the

Contents

Main IMAQ Page Important Information Warranty Copyright Trademarks WARNINGREGARDING USE OF NATIONAL INSTRUMENTS PRODUCTS Conventions Contents Chapter 1 Introduction to IMAQ Vision Chapter 2 Getting Measurement-Ready Images Chapter 3 Grayscale and Color Measurements Chapter 4 Blob Analysis Chapter 5 Machine Vision Page Introduction to IMAQ Vision About IMAQ Vision Documentation and Examples Application Development Environments IMAQ Vision Function Tree Page IMAQ Machine Vision Function Tree Creating IMAQ Vision Applications Chapter1 Introductionto IMAQ Vision Figure1-2. InspectionSteps for Building a Vision Application IMAQVision for LabWindows/CVI User Manual 1-6 ni.com Getting Measurement-Ready Images Set Up Your Imaging System Calibrate Your Imaging System Create an Image Page Source and Destination Images AcquireorReadanImage 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 Page Complex Image Operations Grayscale and Color Measurements Define Regions of Interest Interactively Defining Regions Page Page Page Page Programmatically Defining Regions Defining Regions with Masks Measure Grayscale Statistics Measure Color Statistics Figure3-4. Primary Components of a Color Image Comparing Colors Learning Color Information Choosing the Right Color Information Specifying the Color Information to Learn Using the Entire Image Using a Region in the Image Using Multiple Regions in the Image Choosing a Color Representation Sensitivity Ignoring Learned Colors Blob Analysis Correct Image Distortion Create a Binary Image Improve the Binary Image Removing Unwanted Blobs Separating TouchingBlobs Improving Blob Shapes Make Particle Measurements Page Page Convert Pixel Coordinates to Real-World Coordinates Machine Vision Locate Objects to Inspect UsingEdgeDetectiontoBuildaCoordinateTransform Page Using Pattern Matching to Build a Coordinate Transform Page Chapter5 MachineVision NationalInstruments Corporation 5-7 IMAQVision for LabWindows/CVI User Manual ChoosingaMethodtoBuildtheCoordinateTransform Figure5-4. Buildinga Coordinate Transform Set Search Areas Interactively Defining Regions Programmatically Defining Regions Find Measurement Points Finding Features Using Edge Detection Finding Lines or Circles Figure5-5. Findinga Straight Feature Finding Edge Points Along One Search Contour Finding Edge Points Along Multiple Search Contours Finding Points Using Pattern Matching Defining and Create Good TemplateImages Symmetry Feature detail Positional information Background information Trainingthe Pattern Matching Algorithm Defining a Search Area Setting Matching Parameters and Tolerances Match Mode Minimum Contrast Rotation Angle Ranges Testingthe Search Algorithm on Test Images Using a Ranking Method to Verify Results Finding Points Using Color Pattern Matching Defining and Creating Good Color TemplateImages Color Information Symmetry Feature Detail Positional Information Trainingthe Color Pattern Matching Algorithm Defining a Search Area Setting Matching Parameters and Tolerances Color Sensitivity Search Strategy Color Score Weight Minimum Contrast Rotation Angle Ranges Testingthe 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 Page Calibration Perspective and Nonlinear Distortion Calibration Defining a Calibration Template Defining a Reference Coordinate System Page Page Learning Calibration Information Specifying Scaling Factors Choosing a Region of Interest Choosing a Learning Algorithm Using the Learning Score Learning the Error Map Learning the Correction Table Setting the Scaling Method Calibration Invalidation Simple Calibration Save Calibration Information Attach Calibration Information A Technical Support Resources Web Support NI Developer Zone Customer Education System Integration Worldwide Support Glossary Numbers/Symbols A B C Page D E F G H I Page J K L M N O P Page Q R S T Page Index A B C D E F G H I Page Page L M N O P R S T V W Z