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National Instruments IMAQ Vision for Measurement Studio Correct Image Distortion, Create a Binary Image

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Chapter4 BlobAnalysis

IMAQVision for LabWindows/CVI User Manual 4-2 ni.com

Correct Image Distortion

Ifyou need to make accurate shape measurements based on the blobs in

an image containingperspective and nonlinear distortion errors, correct

the distortion using the calibration information you attached to your

image.U se imaqCorrectCalibratedImage()to correct distorti on 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

Thresholdyour grayscale or color image to create a binary image. Creating

ab inary image separates the objects that you want to inspect from the

background.The threshold operation sets the backgroundpixels to 0 in the

binary image, whiles etting theo bject pixels to a non-zero value. Object

pixelshave a v alue of 1 by default, but you can set the object pixels to any

value or retain their original value.

Youcan use different techniques to threshold your image. If all the

objects of interest in your grayscale image fall within a continuous range

ofintensities and yo u canspeci fy this threshold range manually,use

imaqThreshold()to threshol d your image.

Ifall the objects in your grayscale image are either brighter or darker than

your background, you can use imaqAutoThreshold() toautomatically

determine the optimal threshold range and threshold your image.

Automatic thresholding techniques offer more flexibility than simple

thresholdsbased on fixed ranges. Because automatic thresholding

techniquesdetermine the threshold level according to the image histogram,

theoperation is more independe nt of changes in the overallbrightness and

contrast of the image than a fixedthreshold. These techniques are more

resistant to changes in lighting, which makes them well suited for

automatedinspection tasks.

If your grayscale image contains objects that havemultiple discontinu ous

grayscale values,use imaqMultithreshold() to specify multiple

threshold ranges.

Ifyou 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.

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