National Instruments IMAQTM C

Glossary

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

C

caliper (1) A function in the NI Vision Assistant and in NI Vision Builder for

Automated Inspection that calculates distances, angles, circular fits, and the

center of mass based on positions given by edge detection, particle analysis,

centroid, and search functions.

(2) A measurement function that finds edge pairs along a specified path in

the image. This function performs an edge extraction and then finds edge

pairs based on specified criteria such as the distance between the leading

and trailing edges, edge contrasts, and so forth.

center of mass The point on an object where all the mass of the object could be

concentrated without changing the first moment of the object about

anyaxis.

chroma The color information in a video signal.

chromaticity The combination of hue and saturation. The relationship between

chromaticity and brightness characterizes a color.

closing A dilation followed by an erosion. A closing fills small holes in objects and

smooths the boundaries of objects.

clustering A technique where the image is sorted within a discrete number of classes

corresponding to the number of phases perceived in an image. The gray

values and a barycenter are determined for each class. This process is

repeated until a value is obtained that represents the center of mass for each

phase or class.

CLUT Color lookup table. A table for converting the value of a pixel in an image

into a red, green, and blue (RGB) intensity.

color image An image containing color information, usually encoded in the RGB form.

color space The mathematical representation for a color. For example, color can be

described in terms of red, green, and blue; hue, saturation, and luminance;

or hue, saturation, and intensity.

complex image Stores information obtained from the FFT of an image. The complex

numbers that compose the FFT plane are encoded in 64-bit floating-point

values: 32 bits for the real part and 32 bits for the imaginary part.

connectivity Defines which of the surrounding pixels of a given pixel constitute its

neighborhood.

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