National Instruments IMAQTM Measure Color Statistics

Chapter 3 Making Grayscale and Color Measurements

© National Instruments Corporation 3-7 IMAQ Vision for Visual Basic User Manual

minimum intensity, and maximum intensity. Use

CWMachineVision.LightMeterRectangle to get the pixel

valuestatistics within a rectangular region in an image.

Use CWIMAQVision.Quantify to obtain the following statistics about the

entire image or individual regions in the image: mean intensity, standard

deviation, minimum intensity, maximum intensity, area, and the percentage

of the image that you analyzed. You can specify regions in the image with

a labeled image mask. A labeled image mask is a binary image that has

been processed so that each region in the image mask has a unique intensity

value. Use CWIMAQVision.Label2 to label the image mask.

Use CWIMAQVision.Centroid2 to compute the energy center of the

image, or of a region within an image.

Measure Color Statistics

Most image processing and analysis methods apply to 8-bit and 16-bit

images. However, you can analyze and process individual components of a

color image.

Using CWIMAQVision.ExtractColorPlanes, you can break down

acolor image into various sets of primary components, such as

RGB (Red, Green, and Blue), HSI (Hue, Saturation, and Intensity),

HSL( Hue, Saturation, and Luminance), or HSV (Hue, Saturation, and

Value). Each component becomes an 8-bit or 16-bit image that you can

process like any other grayscale image. Use

CWIMAQVision.ExtractSingleColorPlane toextract a single color

plane from an image. Use CWIMAQVision.ReplaceColorPlanes to

reassemble a color image from a set of three 8-bit or 16-bit images, where

each image becomes one of the three primary components. Figures3-3

and 3-4 illustrate how a color image breaks down into its three components.

Contents

Main Page Important Information Warranty Copyright Trademarks WARNING REGARDING USE OF NATIONAL INSTRUMENTS PRODUCTS Contents About This Manual Chapter 1 Introduction to IMAQ Vision Chapter 2 Getting Measurement-Ready Images Chapter 3 Making Grayscale and Color Measurements Chapter 4 Performing Particle Analysis Chapter 5 Performing Machine Vision Tasks Page Page About This Manual Conventions Related Documentation IMAQ Vision NI Vision Assistant NI Vision Builder for Automated Inspection Other Documentation Introduction to IMAQ Vision About IMAQ Vision Documentation and Examples IMAQ Vision for Visual Basic Organization cwimaq.ocx CWIMAQ Control CWIMAQVision Control CWIMAQViewer Control niocr.ocx NIOCR control cwmv.ocx CWMachineVision control ActiveX Objects Creating IMAQ Vision Applications Chapter 1 Introduction to IMAQ Vision Figure 1-1. General Steps for Designing a Vision Application IMAQ Vision for Visual Basic User Manual 1-6 ni.com Chapter 1 Introduction to IMAQ Vision Figure 1-2. Inspection Steps for Building a Vision Application National Instruments Corporation 1-7 IMAQ Vision for Visual Basic User Manual Getting Measurement-Ready Images Set Up Your Imaging System Calibrate Your Imaging System Create an Image Page Acquire or Read an Image Acquiring an Image One-Shot Acquisition Continuous Acquisition Reading a File Converting an Array to an Image Display an Image Attach Calibration Information Analyze an Image Page Improve an Image Lookup Tables Filters Convolution Filter Nth Order Filter Grayscale Morphology FFT Complex Image Operations Making Grayscale and Color Measurements Define Regions of Interest Defining Regions Interactively Page Page Figure 3-2. Tools Information Defining Regions Programmatically Defining Regions with Masks Measure Grayscale Statistics Measure Color Statistics Figure 3-3. Primary Components of an 32-bit Color Image Figure 3-4. Primary Components of a 64-bit Color Image CWIMAQVision.ColorValueConversion2. Comparing Colors Learning 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 Performing Particle Analysis Create a Binary Image Improve the Binary Image Removing Unwanted Particles Separating Touching Particles Improving Particle Shapes Make Particle Measurements Page Page Page Page Page Page Performing Machine Vision Tas ks Locate Objects to Inspect Using Edge Detection to Build a Coordinate Transformation Page Using Pattern Matching to Build a Coordinate Transformation Page Chapter 5 Performing Machine Vision Tasks National Instruments Corporation 5-7 IMAQ Vision for Visual Basic User Manual Choosing a Method to Build the Coordinate Transformation Figure 5-4. Building a Coordinate Transformation Set Search Areas Defining Regions Interactively Defining Regions Programmatically Find Measurement Points Finding Features Using Edge Detection Finding Lines or Circles Finding Edge Points Along One Search Contour Finding Edge Points Along Multiple Search Contours Finding Points Using Pattern Matching Defining and Creating Effective Template Images Symmetry Feature Detail Positional Information Background Information Training the Pattern Matching Algorithm Defining a Search Area Setting Matching Parameters and Tolerances Match Mode Minimum Contrast Rotation Angle Ranges Testing the Search Algorithm on Test Images Using a Ranking Method to Verify Results Finding Points Using Color Pattern Matching Defining and Creating Effective Color Template Images Color Information Symmetry Feature Detail Positional Information Training the 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 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 Identify Parts Under Inspection Classifying Samples Reading Characters Reading Barcodes Read 1D Barcodes Read Data Matrix Barcode Read PDF417 Barcode Display Results Page Page Calibrating Images Perspective and Nonlinear Distortion Calibration Defining a Calibration Template Defining a Reference Coordinate System 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 Mode Calibration Invalidation Simple Calibration Save Calibration Information Attach Calibration Information Page A Technical Support and Professional Services Glossary Numbers A B Page C D E F G H I Page J K L Page M N O P Q R S T Page Index Numerics A B C D E F G H I K L M N O P R S T U V W Z