National Instruments IMAQTM - page 20

Chapter 2 Getting Measurement-Ready Images

© National Instruments Corporation 2-3 IMAQ Vision for Visual Basic User Manual

• Complex

• 32-bit RGB

• 32-bit HSL

• 64-bit RGB

When you create an image, it is an 8-bit image by default. You can set the

Type property on the image object to change the image type.

When you create an image, no memory is allocated to store the image

pixels. IMAQ Vision methods automatically allocate the appropriate

amount of memory when the image size is modified. For example, methods

that acquire or resample an image alter the image size, so they allocate the

appropriate memory space for the image pixels.

Most methods belonging to the IMAQ Vision library require an input of one

ormore image objects. The number of images a method takes depends on

the image processing function and the type of image you want to use.

IMAQ Vision methods that analyze the image but do not modify the image

contents require the input of one source image. Methods that process the

contents of the image require one or more source images and a destination

image. Exceptions to the preceding statements are methods that take a mask

image as input.

The presence of a MaskImage parameter indicates that the processing or

analysis is dependent on the contents of the mask image. The only pixels

in the source image that are processed are those whose corresponding

pixels in the mask image are non-zero. If a mask image pixel is 0, the

corresponding source image pixel is not processed or analyzed. The mask

image must be an 8-bit image.

If you want to apply a processing or analysis method to the entire image,

do not supply the optional mask image. Using the same image for both the

source image and mask image also has the same effect as not using the

mask image, except in this case the source image must be an 8-bit image.

Most operations between two images require that the images have the same

type and size. However, arithmetic operations work between two different

types of images. For example, an arithmetic operation between an 8-bit

image and 16-bit image results in a 16-bit image.

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