National Instruments IMAQ Vision for Measurement Studio User Manual
™
IMAQ
IMAQ Vision
for Measurement Studio
User Manual
LabWindows/CVI
IMAQ Vision for LabWindows/CVI User Manual
™
May 2001 Edition
Part Number 323022A-01
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Conventions
The following conventions are used in this manual:
» The » symbol leads you through nested menu items and dialog box options
to a final action. The sequence File»Page Setup»Options directs you to
pull down the File menu, select the Page Setup item, and select Options
from the last dialog box.
This icon denotes a note, which alerts you to important information.
bold Bold text denotes items that you must select or click on in the software,
such as menu items and dialog box options. Bold text also denotes
parameter names.
italic Italic text denotes variables, emphasis, a cross reference, or an introduction
to a key concept. This font also denotes text that is a placeholder for a word
or value that you must supply.
monospace
Text in this font denotes text or characters that you should enter from the
keyboard, sections of code, programming examples, and syntax examples.
This font is also used for the proper names of disk drives, paths, directories,
programs, subprograms, subroutines, device names, functions, operations,
variables, filenames and extensions, and code excerpts.
Contents
Chapter 1
Introduction to IMAQ Vision
About IMAQ Vision ......................................................................................................1-1
Documentation and Examples .......................................................................................1-1
Application Development Environments.......................................................................1-2
IMAQ Vision Function Tree..........................................................................................1-2
IMAQ Machine Vision Function Tree...........................................................................1-4
Creating IMAQ Vision Applications.............................................................................1-5
Chapter 2
Getting Measurement-Ready Images
Set Up Your Imaging System ........................................................................................2-1
Calibrate Your Imaging System ....................................................................................2-2
Create an Image .............................................................................................................2-2
Source and Destination Images .......................................................................2-4
Acquire or Read an Image .............................................................................................2-5
Acquiring an Image .........................................................................................2-6
Reading a File..................................................................................................2-6
Converting an Array to an Image ....................................................................2-7
Display an Image ...........................................................................................................2-7
Attach Calibration Information......................................................................................2-8
Analyze an Image ..........................................................................................................2-8
Improve an Image ..........................................................................................................2-9
Lookup Tables .................................................................................................2-9
Filters...............................................................................................................2-10
Convolution Filter .............................................................................2-10
Nth Order Filter.................................................................................2-11
Grayscale Morphology ....................................................................................2-11
FFT ..................................................................................................................2-11
Complex Image Operations ..............................................................2-13
Chapter 3
Grayscale and Color Measurements
Define Regions of Interest .............................................................................................3-1
Interactively Defining Regions........................................................................3-1
Programmatically Defining Regions ...............................................................3-6
Defining Regions with Masks .........................................................................3-6
Measure Grayscale Statistics .........................................................................................3-7
© National Instruments Corporation v IMAQ Vision for LabWindows/CVI User Manual
Contents
Measure Color Statistics................................................................................................ 3-7
Chapter 4
Blob Analysis
Correct Image Distortion............................................................................................... 4-2
Create a Binary Image................................................................................................... 4-2
Improve the Binary Image............................................................................................. 4-3
Make Particle Measurements ........................................................................................ 4-4
Convert Pixel Coordinates to Real-World Coordinates ................................................ 4-7
Chapter 5
Comparing Colors ........................................................................................... 3-8
Learning Color Information ............................................................................ 3-9
Choosing the Right Color Information............................................. 3-9
Specifying the Color Information to Learn ...................................... 3-10
Choosing a Color Representation Sensitivity ................................... 3-12
Ignoring Learned Colors................................................................... 3-13
Removing Unwanted Blobs ............................................................................ 4-3
Separating Touching Blobs............................................................................. 4-4
Improving Blob Shapes................................................................................... 4-4
Machine Vision
Locate Objects to Inspect .............................................................................................. 5-2
Using Edge Detection to Build a Coordinate Transform................................ 5-3
Using Pattern Matching to Build a Coordinate Transform ............................. 5-5
Choosing a Method to Build the Coordinate Transform................................. 5-7
Set Search Areas............................................................................................................ 5-8
Interactively Defining Regions ....................................................................... 5-8
Programmatically Defining Regions............................................................... 5-9
Find Measurement Points ..............................................................................................5-9
Finding Features Using Edge Detection ......................................................... 5-9
Finding Points Using Pattern Matching.......................................................... 5-13
Finding Points Using Color Pattern Matching................................................ 5-18
Finding Lines or Circles ................................................................... 5-9
Finding Edge Points Along One Search Contour.............................5-11
Finding Edge Points Along Multiple Search Contours .................... 5-12
Defining and Create Good Template Images ................................... 5-13
Training the Pattern Matching Algorithm ........................................ 5-15
Defining a Search Area..................................................................... 5-15
Setting Matching Parameters and Tolerances................................... 5-16
Testing the Search Algorithm on Test Images ................................. 5-18
Using a Ranking Method to Verify Results...................................... 5-18
Defining and Creating Good Color Template Images......................5-19
IMAQ Vision for LabWindows/CVI User Manual vi ni.com
Convert Pixel Coordinates to Real-World Coordinates.................................................5-26
Make Measurements ......................................................................................................5-26
Display Results ..............................................................................................................5-28
Chapter 6
Calibration
Perspective and Nonlinear Distortion Calibration .........................................................6-1
Simple Calibration .........................................................................................................6-9
Save Calibration Information.........................................................................................6-10
Attach Calibration Information......................................................................................6-10
Contents
Training the Color Pattern Matching Algorithm...............................5-20
Defining a Search Area .....................................................................5-21
Setting Matching Parameters and Tolerances...................................5-22
Testing the Search Algorithm on Test Images..................................5-24
Finding Points Using Color Location.............................................................. 5-25
Distance Measurements...................................................................................5-26
Analytic Geometry Measurements..................................................................5-27
Instrument Reader Measurements ...................................................................5-27
Defining a Calibration Template.....................................................................6-2
Defining a Reference Coordinate System .......................................................6-2
Learning Calibration Information....................................................................6-5
Specifying Scaling Factors................................................................6-6
Choosing a Region of Interest...........................................................6-6
Choosing a Learning Algorithm .......................................................6-6
Using the Learning Score..................................................................6-7
Learning the Error Map.....................................................................6-8
Learning the Correction Table .......................................................... 6-8
Setting the Scaling Method ...............................................................6-8
Calibration Invalidation ....................................................................6-8
Appendix A
Technical Support Resources
Glossary
Index
© National Instruments Corporation vii IMAQ Vision for LabWindows/CVI User Manual
Introduction to IMAQ Vision
This chapter describes the IMAQ Vision for LabWindows/CVI software
and associated software products, discusses the documentation and
examples available, outlines the IMAQ Vision function organization, and
lists the steps for making a machine vision application.
Note
For information about the system requirements and installation procedure for
IMAQ Vision for LabWindows/CVI, see the IMAQ Vision for Measurement Studio
Release Notes that came with your software.
About IMAQ Vision
IMAQ Vision for Measurement Studio is a National Instruments product
comprised of IMAQ Vision for LabWindows/CVI and IMAQ Vision for
Visual Basic. IMAQ Vision for LabWindows/CVI is a library of C
functions that you can use to develop machine vision and scientific imaging
applications. IMAQ Vision for Visual Basic is a collection of ActiveX
controls that offer the same imaging functionality as IMAQ Vision for
LabWindows/CVI. National Instruments also offers IMAQ Vision for
LabVIEW, which is a library of LabVIEW VIs for developing machine
vision and scientific imaging applications. IMAQ Vision Builder, another
software product from National Instruments, allows you to prototype your
application strategy quickly without having to do any programming.
1
Documentation and Examples
In addition to this manual, several documentation resources are available
to help you create your vision application:
• IMAQ Vision Concepts Manual—If you are new to machine vision
and imaging, read this manual to understand the concepts behind
IMAQ Vision.
• IMAQ Vision for LabWindows/CVI function reference—If you need
information about IMAQ Vision functions while creating your
application, refer to this help file. Access this file from the Start menu
by selecting Programs»National Instruments»Vision»
© National Instruments Corporation 1-1 IMAQ Vision for LabWindows/CVI User Manual
Chapter 1 Introduction to IMAQ Vision
Documentation»IMAQ Vision for LabWindows/CVI Function
Reference.
• Example programs—If you want examples of how to create specific
applications, go to
• Application Notes—If you want to know more about advanced
IMAQ Vision concepts and applications, refer to the Application
Notes located on the National Instruments Web site at
ni.com/appnotes.nsf/
• NI Developer Zone (NIDZ)—If you want even more information about
developing your vision application, visit the NI Developer Zone at
ni.com/zone.
tutorials, technical presentations, the Instrument Driver Network, a
measurement glossary, an online magazine, a product advisor, and a
community area where you can share ideas, questions, and source code
with vision developers around the world.
cvi\samples\vision
The NI Developer Zone contains example programs,
Application Development Environments
This release of IMAQ Vision for LabWindows/CVI supports the following
Application Development Environments (ADEs) for Windows
2000/NT/Me/9x.
• LabWindows/CVI version 5.0.1 and higher
• Borland C++ Builder 3.0 and higher
• Microsoft Visual C/C++ version 6.0 and higher
.
Note
Although IMAQ Vision has been tested and found to work with these ADEs, other
ADEs may also work.
IMAQ Vision Function Tree
The IMAQ Vision function tree (
classes corresponding to groups or types of functions. Table 1-1 lists the
IMAQ Vision function types and gives a description of each type.
IMAQ Vision for LabWindows/CVI User Manual 1-2 ni.com
NIVision.lfp
) contains separate
Chapter 1 Introduction to IMAQ Vision
Table 1-1.
IMAQ Vision Function Types
Function Type Description
Image
Management
Memory
Functions that create space in memory for images and perform basic image
manipulation.
A function that returns memory you no longer need to the operating system.
Management
Error
Management
Functions that set the current error, return the name of the function in which the
last error occurred, return the error code of the last error, and clear any pending
errors.
Acquisition Functions that acquire images through an IMAQ hardware device.
Display Functions that cover all aspects of image visualization and image window
management.
Overlay Functions that create and manipulate overlays.
Regions of
Functions that create and manipulate regions of interest.
Interest
File I/O Functions that read and write images to and from files.
Calibration Functions that learn calibration information and correct distorted images.
Image Analysis
Functions that compute the centroid of an image, profile of a line of pixels,
and the mean line profile. This type also includes functions that calculate the
pixel distribution and statistical parameters of an image.
Grayscale
Functions for grayscale image processing and analysis.
Processing
Binary
Functions for binary image processing and analysis.
Processing
Color
Functions for color image processing and analysis.
Processing
Pattern
Functions that learn patterns and search for patterns in images.
Matching
Caliper Functions designed for gauging, measurement, and inspection applications.
Operators Functions that perform arithmetic, logic, and comparison operations with
two images or with an image and a constant value.
Analytic
Functions that perform basic geometric calculations on an image.
Geometry
© National Instruments Corporation 1-3 IMAQ Vision for LabWindows/CVI User Manual
Chapter 1 Introduction to IMAQ Vision
Table 1-1. IMAQ Vision Function Types (Continued)
Function Type Description
Frequency
Domain
Analysis
Barcode A function that reads a barcode.
LCD Functions that find and read seven-segment LCD characters.
Meter Functions that return the arc information of a meter and read the meter.
Utilities Functions that return structures, and a function that returns a pointer to
Obsolete Functions that are no longer necessary but may exist in older applications.
Functions for the extraction and manipulation of complex planes. Functions of
this type perform FFTs, inverse FFTs, truncation, attenuation, addition,
subtraction, multiplication, and division of complex images.
predefined convolution matrices.
IMAQ Machine Vision Function Tree
The IMAQ Machine Vision function tree (
contains separate classes corresponding to groups or types of functions.
Table 1-2 lists the IMAQ Machine Vision function types and gives a
description of each type.
Table 1-2. IMAQ Machine Vision Function Types
Function Type Description
Coordinate Transform Functions that find coordinate transforms based on image contents.
NIMachineVision.fp
)
Count and Measure Objects A function that counts and measures objects in an image.
Find Patterns A function that finds patterns in an image.
Locate Edges Functions that locate different types of edges in an image.
Measure Distances Functions that measure distances between objects in an image.
Measure Intensities Functions that measure light intensities in various shaped regions
within an image.
Select Region of Interest Functions that allow a user to select a specific region of interest in
an image.
IMAQ Vision for LabWindows/CVI User Manual 1-4 ni.com
Creating IMAQ Vision Applications
Figures 1-1 and 1-2 illustrate the steps for creating an application with
IMAQ Vision. Figure 1-1 describes the general steps to designing a Vision
application. The last step in Figure 1-1 is expanded upon in Figure 1-2.
You can use a combination of the items in the last step to create your IMAQ
Vision application. For more information about items in either diagram,
see the corresponding chapter listed to the right of the item.
Note
Diagram items enclosed with dashed lines are optional steps.
Set Up Your Imaging System
Chapter 1 Introduction to IMAQ Vision
Chapter 2:
Measurement-Ready
Getting
Images
Calibrate Your Imaging System
Create an Image
Acquire or Read an Image
Display an Image
Attach Calibration Information
Analyze an Image
Improve an Image
Improve an Image
Make Measurements in an Image Using
1
Grayscale or Color Measurements, and/or
2
Blob Analysis, and/or
3
Machine Vision
Chapter 6:
Calibration
Figure 1-1. General Steps to Designing a Vision Application
© National Instruments Corporation 1-5 IMAQ Vision for LabWindows/CVI User Manual
Chapter 1 Introduction to IMAQ Vision
1
Chapter 4:
Blob Analysis
Chapter 3:
Grayscale and Color
Measurements
Make Particle Measurements
Convert Pixel Coordinates to
Measure
Grayscale Statistics
2
Correct Image Distortion
Create a Binary Image
Improve a Binary Image
Real-World Coordinates
Define Regions of Interest
Measure
Color Statistics
Locate Objects to Inspect
Find Measurement Points
Convert Pixel Coordinates to
Real-World Coordinates
3
Set Search Areas
Make Measurements
Display Results
Chapter 5:
Machine Vision
Figure 1-2. Inspection Steps for Building a Vision Application
IMAQ Vision for LabWindows/CVI User Manual 1-6 ni.com
Getting Measurement-Ready
Images
This chapter describes how to set up your imaging system, acquire and
display an image, analyze the image, and prepare the image for additional
processing.
Set Up Your Imaging System
Before you acquire, analyze, and process images, you must set up your
imaging system. The manner in which you set up your system depends on
your imaging environment and the type of analysis and processing you
need to do. Your imaging system should produce images with high enough
quality so that you can extract the information you need from the images.
Follow the guidelines below to setup your imaging system.
1. Determine the type of equipment you need given your space
constraints and the size of the object you need to inspect. For more
information, see Chapter 3, System Setup and Calibration,ofthe
IMAQ Vision Concepts Manual.
a. Make sure your camera sensor is large enough to satisfy your
minimum resolution requirement.
b. Make sure your lens has a depth of field high enough to keep all
of your objects in focus regardless of their distance from the lens.
Also, make sure your lens has a focal length that meets your
needs.
c. Make sure your lighting provides enough contrast between the
object under inspection and the background for you to extract the
information you need from the image.
2. Position your camera so that it is parallel to the object under
inspection. If your camera acquires images of the object from an angle,
perspective errors occur. You can compensate for these errors with
software, but using a parallel inspection angle obtains the fastest and
most accurate results.
2
© National Instruments Corporation 2-1 IMAQ Vision for LabWindows/CVI User Manual
Chapter 2 Getting Measurement-Ready Images
3. Select an image acquisition device that meets your needs. National
Instruments offers several image acquisition (IMAQ) devices, such as
analog color and monochrome IMAQ devices as well as digital
devices. Visit
devices.
4. Configure the driver software for your image acquisition device. If
you have a National Instruments image acquisition device, configure
your NI-IMAQ driver software through Measurement & Automation
Explorer (MAX). Open MAX by double-clicking the Measurement &
Automation Explorer icon on your desktop. For more information,
see the NI-IMAQ User Manual and the MAX online help.
ni.com/imaq
Calibrate Your Imaging System
After you set up your imaging system, you may want to calibrate your
system. Calibrate your imaging system to assign real-world coordinates to
pixel coordinates and compensate for perspective and nonlinear errors
inherent in your imaging system.
Perspective errors occur when your camera axis is not perpendicular to the
object under inspection. Nonlinear distortion may occur from aberrations
in the camera lens. Perspective errors and lens aberrations cause images to
appear distorted. This distortion misplaces information in an image, but it
does not necessarily destroy the information in the image.
for more information about IMAQ
Use simple calibration if you only want to assign real-world coordinates to
pixel coordinates. Use perspective and nonlinear distortion calibration if
you need to compensate for perspective errors and nonlinear lens distortion.
For detailed information about calibration, see Chapter 6, Calibration.
Create an Image
To create an image in IMAQ Vision for LabWindows/CVI, call
imaqCreateImage()
use when calling other IMAQ Vision functions. The only limitation to the
size and number of images you can acquire and process is the amount of
memory on your computer. When you create an image, specify the type of
the image. Table 2-1 lists the valid image types.
IMAQ Vision for LabWindows/CVI User Manual 2-2 ni.com
. This function returns an image reference you can
Chapter 2 Getting Measurement-Ready Images
Va lu e Description
IMAQ_IMAGE_U8
IMAQ_IMAGE_I16
IMAQ_IMAGE_SGL
IMAQ_IMAGE_COMPLEX
IMAQ_IMAGE_RGB
IMAQ_IMAGE_HSL
Table 2-1.
IMAQ Vision for LabWindows/CVI Image Types
8 bits per pixel—unsigned, standard monochrome
16 bits per pixel—signed, monochrome
32 bits per pixel—floating point, monochrome
2 × 32 bits per pixel—floating point, native format after a Fast
Fourier Transform (FFT)
32 bits per pixel—standard color
32 bits per pixel—color
If you plan to use filtering or blob analysis functions on the image, set the
appropriate border size for the image. The default border size is 3.
When you create an image, IMAQ Vision creates an internal image
structure to hold properties of the image, such as its name and border size.
However, no memory is allocated to store the image pixels at this time.
IMAQ Vision functions automatically allocate the appropriate amount of
memory when the image size is modified. For example, functions that
acquire or resample an image alter the image size, so they allocate the
appropriate memory space for the image pixels. The return value of
imaqCreateImage()
is a pointer to the image structure. Supply this
pointer as an input to all subsequent IMAQ Vision functions.
Most functions belonging to the IMAQ Vision library require one or more
image pointers. The number of image pointers a function takes depends on
the image processing function and the type of image you want to use. Some
IMAQ Vision functions act directly on the image and require only one
image pointer. Other functions that process the contents of images require
pointers to the source image(s) and to a destination image.
You can create multiple images by executing
imaqCreateImage()
as
many times as you want. Determine the number of required images through
an analysis of your intended application. The decision is based on different
processing phases and your need to keep the original image (after each
processing step).
At the end of your application, dispose of each image that you created using
imaqDispose()
© National Instruments Corporation 2-3 IMAQ Vision for LabWindows/CVI User Manual
.
Chapter 2 Getting Measurement-Ready Images
Source and Destination Images
Some IMAQ Vision functions that modify the contents of an image have
source image and destination image input parameters. The source image
receives the image to process. The destination image receives the
processing results. The destination image can receive either another image
or the original, depending on your goals. If you do not want the contents of
the original image to change, use separate source and destination images.
If you want to replace the original image with the processed image, pass the
same image as both the source and destination.
Depending on the function, the image type of the destination image can be
the same or different than the image type of the source image. The function
descriptions in the IMAQ Vision for LabWindows/CVI function reference
help include the type of images you can use as image inputs and outputs.
IMAQ Vision resizes the destination image to hold the result if the
destination is not the appropriate size.
The following examples illustrate source and destination images with
imaqTranspose()
•
imaqTranspose(myImage, myImage);
This function creates a transposed image using the same image for the
source and destination. The contents of
•
imaqTranspose(myTransposedImage, myImage);
This function creates a transposed image and stores it in a destination
different from the source. The
and
myTransposedImage
:
change.
myImage
myImage
image remains unchanged,
contains the result.
Functions that perform arithmetic or logical operations between two
images have two source images and a destination image. You can perform
an operation between two images and then either store the result in a
separate destination image or in one of the two source images. In the
latter case, make sure you no longer need the original data in the source
image before storing the result over the data.
The following examples show the possible combinations using
imaqAdd()
•
imaqAdd(myResultImage, myImageA, myImageB);
This function adds two source images (
stores the result in a third image (
:
myImageA
myResultImage
and
myImageB
). Both source
)and
images remain intact after processing.
IMAQ Vision for LabWindows/CVI User Manual 2-4 ni.com
Chapter 2 Getting Measurement-Ready Images
•
imaqAdd(myImageA, myImageA, myImageB);
This function adds two source images and stores the result in the first
source image.
•
imaqAdd(myImageB, myImageA, myImageB);
This function adds two source images and stores the result in the
second source image.
Most operations between two images require that the images have the
same type and size. However, some arithmetic operations can work
between two different types of images (for example, 8-bit and 16-bit).
Some functions perform operations that populate an image. Examples of
this type of operation include reading a file, acquiring an image from an
IMAQ device, or transforming a 2D array into an image. This type of
function can modify the size of an image.
Some functions take an additional mask parameter. The presence of a
mask parameter indicates that the processing or analysis is dependent on
the contents of another image (the image mask). The only pixels in the
source image that are processed are those whose corresponding pixels in
the image mask are non-zero. If an image mask pixel is 0, the
corresponding source image pixel is not processed or analyzed. The image
mask must be an 8-bit image.
If you want to apply a processing or analysis function to the entire image,
pass NULL for the image mask. Passing the same image to both the source
image and image mask also gives the same effect as passing NULL for the
image mask, except in this case the source image must be an 8-bit image.
AcquireorReadanImage
After you create an image reference, you can acquire an image into your
imaging system in three ways. You can acquire an image with a camera
through your image acquisition device, load an image from a file stored on
your computer, or convert the data stored in a 2D array to an image.
Functions that acquire images, load images from file, or convert data from
a 2D array automatically allocate the memory space required to
accommodate the image data.
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Chapter 2 Getting Measurement-Ready Images
Acquiring an Image
Use one of the following methods to acquire images with a National
Instruments image acquisition (IMAQ) device:
• Acquire a single image using
this function, it initializes the IMAQ device and acquires the next
incoming video frame. Use this function for low-speed single capture
applications where ease of programming is essential.
• Acquire a single image using
function, it acquires the next incoming video frame on an IMAQ
device you have already initialized using
i
mgSessionOpen()
applications.
• Acquire images continually through a grab acquisition. Grab functions
perform high-speed acquisitions that loop continually on one buffer.
Use
imaqSetupGrab()
return a copy of the current image. Use
stop the acquisition.
• Acquire a fixed number of images using a sequence acquisition. Set up
the acquisition using
imaqStartAcquisition()
requested during setup. If you want to acquire only certain images,
supply
frames to skip after each acquired frame.
• Acquire images continually through a ringed buffer acquisition. Set up
the acquisition using
imaqStartAcquisition()
acquired ring buffer. To get an image from the ring, call
imaqExtractFromRing()orimaqCopyRing()
imaqStopAcquisition()
imaqEasyAcquire()
imaqSnap()
. Use this function for high-speed single capture
to start the acquisition. Use
imaqSetupSequence()
to acquire the number of images you
imaqSetupSequence()
imaqSetupRing()
to start acquiring images into the
to stop the acquisition.
. When you call
. When you call this
imgInterfaceOpen()
imaqGrab()
imaqStopAcquisition()
and
to
to
.Use
with a table describing the number of
.Use
.Use
Note
You must use the
imgClose()
to release resources associated with the image
acquisition device.
Reading a File
Use
imaqReadFile()
computer into the image reference. You can read from image files stored in
severalstandardformats:BMP,TIFF,JPEG,PNG,andAIPD.The
software automatically converts the pixels it reads into the type of image
you pass in.
IMAQ Vision for LabWindows/CVI User Manual 2-6 ni.com
to open and read data from a file stored on your
Chapter 2 Getting Measurement-Ready Images
Use
imaqReadVisionFile()
information, such as calibration information, template information for
pattern matching, or overlay information. For more information about
pattern matching templates and overlays, see Chapter 5, Machine Vision.
You can also use
properties—image size, recommended image type, and calibration
units—without actually reading all the image data.
Converting an Array to an Image
Use
imaqArrayToImage()
also use
imaqImageToArray()
Display an Image
Display an image in an external window using
You can display images in 16 different external windows. Use the other
display functions to configure the appearance of each external window.
Properties you can set include whether the window has scroll bars, is
resizable, or has a title bar. You can also use
position the external image window at a particular location on you monitor.
See the IMAQ Vision for LabWindows/CVI function reference for a
complete list of display functions.
to open an image file containing additional
imaqGetFileInfo()
to convert a 2D array to an image. You can
to convert an image to a 2D array.
to retrieve image
imaqDisplayImage()
imaqMoveWindow()
.
to
Note
Image windows are not LabWindows/CVI panels. They are managed directly by
IM AQ Vis ion.
You can use a color palette to display grayscale images by applying a color
palette to the window. Use
imaqSetWindowPalette()
to set predefined
color palettes. For example, if you need to display a binary image—an
image containing particle regions with pixel values of 1 and a background
region with pixel values of 0—apply the predefined binary palette. For
more information about color palettes, see the Chapter 2, Display,ofthe
IMAQ Vision Concepts Manual.
Note
At the end of your application, you should close all open external windows using
imaqCloseWindow()
© National Instruments Corporation 2-7 IMAQ Vision for LabWindows/CVI User Manual
.
Chapter 2 Getting Measurement-Ready Images
Attach Calibration Information
If you want to attach the calibration information of the current setup to
each image you acquire, use
function takes in a source image containing the calibration information and
a destination image that you want to calibrate. The output image is your
inspection image with the calibration information attached to it. For
detailed information about calibration, see Chapter 6, Calibration.
Note
Because calibration information is part of the image, it is propagated throughout
the processing and analysis of the image. Functions that modify the image size (such as
geometrical transforms) void the calibration information. Use
to save the image and all of the attached calibration information to a file.
Analyze an Image
Once you acquire and display an image, you may want to analyze the
contents of the image for the following reasons:
• To determine whether the image quality is high enough for your
inspection task.
• To obtain the values of parameters that you want to use in processing
functions during the inspection process.
imaqCopyCalibrationInfo()
imaqWriteVisionFile()
.This
The histogram and line profile tools can help you analyze the quality of
your images.
Use
imaqHistogram()
image. Use the histogram of the image to analyze two important criteria
that define the quality of an image—saturation and contrast. If your image
is underexposed (does not have enough light) the majority of your pixels
will have low intensity values, which appear as a concentration of peaks on
the left side of your histogram. If your image is overexposed (has too much
light) the majority of your pixels will have a high intensity values, which
appear as a concentration of peaks on the right side of your histogram. If
your image has an appropriate amount of contrast, your histogram will have
distinct regions of pixel concentrations. Use the histogram information to
decide if the image quality is high enough to separate objects of interest
from the background.
If the image quality meets your needs, use the histogram to determine the
range of pixel values that correspond to objects in the image. You can use
IMAQ Vision for LabWindows/CVI User Manual 2-8 ni.com
to analyze the overall grayscale distribution in the
Chapter 2 Getting Measurement-Ready Images
this range in processing functions, such as determining a threshold range
during blob analysis.
If the image quality does not meet your needs, try to improve the imaging
conditions to get the desired image quality. You may need to re-evaluate
and modify each component of your imaging setup: lighting equipment
and setup, lens tuning, camera operation mode, and acquisition board
parameters. If you reach the best possible conditions with your setup but
the image quality still does not meet your needs, try to improve the image
quality using the image processing techniques described in the Improve an
Image section.
Use
image, or use
one-dimensional path in the image. By looking at the pixel distribution, you
can determine if the image quality is high enough to provide you with sharp
edges at object boundaries. Also, you can determine if the image is noisy,
and identify the characteristics of the noise.
If the image quality meets your needs, use the pixel distribution information
to determine some parameters of the inspection functions you want to use.
For example, use the information from the line profile to determine the
strength of the edge at the boundary of an object. You can input this
information into
line.
Improve an Image
Using the information you gathered from analyzing your image, you may
want to improve the quality of your image for inspection. You can improve
your image with lookup tables, filters, grayscale morphology, and Fast
Fourier transforms.
Lookup Tables
Apply lookup table (LUT) transformations to highlight image details in
areas containing significant information at the expense of other areas.
A LUT transformation converts input grayscale values in the source image
into other grayscale values in the transformed image. IMAQ Vision
provides four functions that directly or indirectly apply lookup tables to
images:
•
imaqLineProfile()
imaqROIProfile()
imaqEdgeTool()
imaqMathTransform()
replacing them with values from a predefined lookup table. IMAQ
Vision has seven predefined lookup tables based on mathematical
to get the pixel distribution along a line in the
to get the pixel distribution along a
to find the edges of objects along the
—Converts the pixel values of an image by
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Chapter 2 Getting Measurement-Ready Images
transformations. For more information about these lookup tables, see
Chapter 5, Image Processing,intheIMAQ Vision Concepts Manual.
•
imaqLookup()
them with values from a user-defined lookup table.
•
imaqEqualize()
given grayscale range. Use IMAQ Equalize to increase the contrast in
images containing few grayscale values.
•
imaqInverse()
compute the negative of the image. For example, use
before applying an automatic threshold to your image if the
background pixels are brighter than the object pixels.
Filters
Filter your image when you need to improve the sharpness of transitions in
the image or increase the overall signal-to-noise ratio of the image. You can
choose either a lowpass or highpass filter depending on your needs.
Lowpass filters remove insignificant details by smoothing the image,
removing sharp details, and smoothing the edges between the objects
and the background. You can use
lowpass filter with
—Converts the pixel values of an image by replacing
—Distributes the grayscale values evenly within a
—Inverts the pixel intensities of an image to
imaqInverse()
imaqLowpass()
imaqConvolve()orimaqNthOrderFilter()
or define your own
.
Highpass filters emphasize details, such as edges, object boundaries, or
cracks. These details represent sharp transitions in intensity value. You can
define your own highpass filter with
imaqNthOrderFilter()
imaqEdgeFilter()orimaqCannyEdgeFilter()
imaqEdgeFilter()
, or you can use a predefined highpass filter with
function allows you to find edges in an image using
imaqConvolve()
or
.The
predefined edge detection kernels, such as the Sobel, Prewitt, and Roberts
kernels.
Convolution Filter
The
imaqConvolve()
lowpass and highpass filters. Each filter is defined by a kernel of
coefficients. Use
predefined kernels do not meet your needs, define your own custom filter
using a 2D array of floating point numbers.
IMAQ Vision for LabWindows/CVI User Manual 2-10 ni.com
function allows you to use a predefined set of
imaqGetKernel()
to retrieve predefined kernels. If the
Nth Order Filter
The
highpass filter depending on the value of N that you choose. One specific
Nth order filter, the median filter, removes speckle noise, which appears as
small black and white dots. Use
filter. For more information about Nth order filters, see Chapter 5, Image
Processing,oftheIMAQ Vision Concepts Manual.
Grayscale Morphology
Perform grayscale morphology when you want to filter grayscale
features of an image. Grayscale morphology helps you remove or
enhance isolated features, such as bright pixels on a dark background.
Use these transformations on a grayscale image to enhance non-distinct
features before thresholding the image in preparation for blob analysis.
imaqNthOrderFilter()
Chapter 2 Getting Measurement-Ready Images
function allows you to define a lowpass or
imaqMedianFilter()
to apply a median
FFT
Use
imaqGrayMorphology()
transformations:
• Erosion—Reduces the brightness of pixels that are surrounded by
neighbors with a lower intensity.
• Dilation—Increases the brightness of pixels surrounded by neighbors
with a higher intensity. A dilation has the opposite effect as an erosion.
• Opening—Removes bright pixels isolated in dark regions and smooths
boundaries.
• Closing—Removes dark pixels isolated in bright regions and smooths
boundaries.
• Proper-opening—Removes bright pixels isolated in dark regions and
smooths the inner contours of particles.
• Proper-closing—Removes dark pixels isolated in bright regions and
smooths the inner contours of particles.
• Auto-median—Generates simpler particles that have fewer details.
For more information about grayscale morphology transformations, see
Chapter 5, Image Processing,oftheIMAQ Vision Concepts Manual.
Use the Fast Fourier Transform (FFT) to convert an image into its
frequency domain. In an image, details and sharp edges are associated
with mid to high spatial frequencies because they introduce significant
gray-level variations over short distances. Gradually varying patterns are
associated with low spatial frequencies.
to perform one of the following seven
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Chapter 2 Getting Measurement-Ready Images
An image can have extraneous noise, such as periodic stripes, introduced
during the digitization process. In the frequency domain, the periodic
pattern is reduced to a limited set of high spatial frequencies. Also, the
imaging setup may produce non-uniform lighting of the field of view,
which produces an image with a light drift superimposed on the
information you want to analyze. In the frequency domain, the light drift
appears as a limited set of low frequencies around the average intensity of
the image (DC component).
Youcanusealgorithmsworkinginthefrequencydomaintoisolateand
remove these unwanted frequencies from your image. Follow these steps to
obtain an image in which the unwanted pattern has disappeared but the
overall features remain:
1. Use
imaqFFT()
frequency domain. This function computes the Fast Fourier Transform
(FFT) of the image and results in a complex image representing the
frequency information of your image.
2. Improve your image in the frequency domain with a lowpass or
highpass frequency filter. Specify which type of filter to use with
imaqAttenuate()orimaqTruncate()
noise, details, textures, and sharp edges in an image. Highpass filters
emphasize details, textures, and sharp edges in images, but they also
emphasize noise.
• Lowpass attenuation—The amount of attenuation is directly
proportional to the frequency information. At low frequencies,
there is little attenuation. As the frequencies increase, the
attenuation increases. This operation preserves all of the zero
frequency information. Zero frequency information corresponds
to the DC component of the image or the average intensity of
the image in the spatial domain.
• Highpass attenuation—The amount of attenuation is inversely
proportional to the frequency information. At high frequencies,
there is little attenuation. As the frequencies decrease, the
attenuation increases. The zero frequency component is removed
entirely.
• Lowpass truncation—Specify a frequency. The frequency
components above the ideal cutoff frequency are removed, and the
frequencies below it remain unaltered.
• Highpass truncation—Specify a frequency. The frequency
components above the ideal cutoff frequency remain unaltered,
and the frequencies below it are removed.
to convert an image from the spatial domain to the
. Lowpass filters smooth
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Chapter 2 Getting Measurement-Ready Images
3. To transform your image back to the spatial domain, use
imaqInverseFFT()
.
Complex Image Operations
The
imaqExtractComplexPlane()
imaqReplaceComplexPlane()
and update independently the real and imaginary planes of a complex
image. You can also convert planes of a complex image to an array
and back with
imaqArrayToComplexPlane()
imaqComplexPlaneToArray()
and
functions allow you to access, process,
and
.
© National Instruments Corporation 2-13 IMAQ Vision for LabWindows/CVI User Manual
Grayscale and Color
Measurements
This chapter describes how to take measurements from grayscale and color
images. You can make inspection decisions based on image statistics, such
as the mean intensity level in a region. Based on the image statistics, you
can perform many machine vision inspection tasks on grayscale or color
images, such as detecting the presence or absence of components, detecting
flaws in parts, and comparing a color component with a reference.
Figure 3-1 illustrates the basic steps involved in making grayscale and
color measurements.
3
Define Regions of Interest
Figure 3-1. Steps to Taking Grayscale and Color Measurements
Define Regions of Interest
A region of interest (ROI) is an area of an image in which you want to
focus your image analysis. You can define an ROI interactively,
programmatically, or with an image mask.
Interactively Defining Regions
You can interactively define an ROI in a window that displays an image.
Use the tools from the IMAQ Vision tools palette to interactively define and
manipulate an ROI. Table 3-1 describes each of the tools and the manner in
which you use them.
Measure
Grayscale Statistics
Measure
Color Statistics
© National Instruments Corporation 3-1 IMAQ Vision for LabWindows/CVI User Manual
Chapter 3 Grayscale and Color Measurements
Table 3-1. Tools Palette Functions
Icon Too l N a me Function
Selection Tool Select an ROI in the image and adjust the position of its control
points and contours.
Action: Click on the desired ROI or control points.
Point Select a pixel in the image.
Action: Click on the desired position.
Line Drawalineintheimage.
Action: Click on the initial position and click again on the final
position.
Rectangle Draw a rectangle or square in the image.
Action: Click on one corner and drag to the opposite corner.
Rotated Rectangle Draw a rotated rectangle in the image.
Action: Click on one corner and drag to the opposite corner to
create the rectangle. Then, click on the lines inside the rectangle
anddragtoadjusttherotationangle.
Oval Draw an oval or circle in the image.
Action: Click on the center position and drag to the desired size.
Annulus Draw an annulus in the image.
Action: Click on the center position and drag to the desired size.
Adjust the inner and outer radii, and adjust the start and end
angle.
Broken Line Drawabrokenlineintheimage.
Action: Click to place a new vertex and double-click to complete
the ROI element.
Polygon Drawapolygonintheimage.
Action: Click to place a new vertex and double-click to complete
the ROI element.
Freehand Line Draw a freehand line in the image.
Action: Click on the initial position, drag to the desired shape and
release the mouse button to complete the shape.
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Chapter 3 Grayscale and Color Measurements
Table 3-1. Tools Palette Functions (Continued)
Icon Too l N a me Function
Freehand Draw a freehand region in the image.
Action: Click on the initial position, drag to the desired shape and
release the mouse button to complete the shape.
Zoom Zoom-in or zoom-out in an image.
Action: Click on the image to zoom in. Hold down <Shift> and
clicktozoomout.
Pan Panaroundanimage.
Action: Click on an initial position, drag to the desired position
and release the mouse button to complete the pan.
Hold down <Shift> while drawing an ROI if you want to constrain the ROI
to the horizontal, vertical, or diagonalaxes when possible. Use the selection
tool to position an ROI by its control points or vertices. ROIs are context
sensitive, meaning that the cursor actions differ depending on the ROI with
which you interact. For example, if you move your cursor over the side of
a rectangle, the cursor changes to indicate that you can click and drag the
side to resize the rectangle. If you want to draw more than one ROI in a
window, hold down <Ctrl> while drawing additional ROIs.
You can display the IMAQ Vision tools palette as part of an ROI constructor
window or in a separate, floating window. Follow these steps to invoke an
ROI constructor and define an ROI from within the ROI constructor
window:
1. Use
imaqConstructROI()
todisplayanimageandthetoolspalette
in an ROI constructor window, as shown in Figure 3-2.
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Chapter 3 Grayscale and Color Measurements
2. Select an ROI tool from the tools palette.
3. Draw an ROI on your image. Resize and reposition the ROI until it
designates the area you want to inspect.
4. Click the OK button to output a descriptor of the region you selected.
You can input the ROI descriptor into many analysis and processing
functions. You can also convert the ROI descriptor into an image mask,
which you can use to process selected regions in the image. Use
imaqROIToMask()
Figure 3-2. ROI Constructor
to convert the ROI descriptor into an image mask.
The tools palette, shown in Figure 3-3, automatically transforms from the
palette on the left to the palette on the right when you manipulate an ROI
tool in an image window. The palette on the right displays the
characteristics of the ROI you are drawing.
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