|Introduction to Machine Vision and Image Acquisition
|This lesson introduces machine vision and provides an overview of the components in a machine vision system.
|Introduction to Lighting, Camera, and Optics
|In this lesson, you will learn about the fundamentals and purpose of lighting, cameras, lenses, and optical accessories. You also will learn how to select and use each of these components.
|Machine Vision Solution Strategies
|In this lesson, you will learn about various hardware options when building a machine vision system. You also will learn about a variety of options for lighting, camera, and optics, and about the NI platforms for machine vision. You then learn how to choose and design the hardware portion of your vision system.
|Acquiring and Displaying Images in LabVIEW
|In this lesson, you will learn how to acquire and display images in LabVIEW.
|Getting Measurement-Ready Images
|In this lesson, you learn will how to prepare an acquired image for measurements in LabVIEW. You will learn how to analyze the image using a histogram, improve the contrast using a lookup table, and enhance its features using gray morphology and filters.
|Performing Particle Analysis
|This lesson covers how to perform particle analysis on an image. You learn how to create a binary image using a threshold, prepare the binary image using morphology and particle filters, and obtain several particle measurements.
|Machine Vision Functions
|In this lesson, you will learn how to perform various machine vision functions on an image. You will learn how to set up a coordinate system using edge detection or pattern matching. You also will learn how to make a variety of distance and analytic geometry measurements on objects in your image.
|This lesson covers how to get measurements in real-world units by calibrating the image.
|Machine Vision Inspections
|In this lesson, you will learn how to perform a variety of machine vision inspections. You will learn how to make measurements for metrology, inspect for presence or absence, inspect for defects, identify parts using bar codes and optical character recognition (OCR), use optical character verification (OCV), process color images, and more.