Greg Hollows
Edmund Optics
Barrington, N.J.

Glenn Archer
Epic Vision Solutions
St. Louis, Mo.

With some help from machine vision systems, automated mechanical systems can align components, read barcodes, guide manipulators, and inspect their own work. Vision and mechanical systems can share the same sensor to measure, find, and orient objects. Without machine vision, engineers must employ additional components such as encoders, proximity sensors, limit switches, and keyways. Recognizing how a machine vision system works, what factors can alter its capabilities, and how to choose components eases integration into a motion control application.

Piecing parts together

The heart of a machine vision system is the lens-camera combination, and each is specified separately. Engineers must choose a lens based on application constraints and a camera based on the control system. Illumination is also important as it provides contrast between objects; area sources, ring lights, incandescent bulbs, and LEDs all provide illumination.

Besides these elements, there must be a component to capture the steady stream of image data that the camera outputs. Frame grabbers do just this. These boards plug into an expansion-bus slot on a host computer and contain on-board intelligence and memory. To define frame grabber parameters such as frame rates and capture triggers, end users can take advantage of drivers in software. An alternative to using frame grabber boards for image capture is utilizing hardware built into the computer and camera.

A host computer is then needed to run image acquisition and processing software. While commercial-offthe-shelf software is easy to use and requires little programming knowledge, custom application software may help a system operate more efficiently. However, customizing software can consume at least half of development time. Once software is in place, a machine vision system forwards collected information to a motion control system.

Managing constraints

Choosing the right machine vision components begins by defining an application and its constraints. For instance, a driverless vehicle restricts a vision system differently than a pick-and-place robot assembling printed circuit boards. These constraints, as well as desired results, influence system setup.

Resolution, the total number of pixels in an image, is determined by dividing the largest object s physical size by the smallest critical dimension.

Area and line scans are constrained by a camera and object s relative motion. Unlike machine vision cameras, film cameras have an area-scan format, meaning they acquire an entire image, or area, at once. They are used when the object can pause (by stopping directly, tracking it with the camera, or pausing it with a short-duration stroboscopic flash) during the exposure. Line-scan cameras, on the other hand, read one line of pixels after another. A rastered image appears when the object moves past a sensor along a line perpendicular to the pixels. These cameras are employed when objects move past at a steady high speed.

Image distance is the length between a lens and image plane. For large format and high-magnification lenses, image distance constrains camera-mounting space.

Image contrast is the quantitative difference between bright and dark pixels. It provides information contained in an image and depends on color, illumination, lens quality, and a camera s electronic properties. Re-call that image sensors are linear sensors, whereas human eyes are logarithmic sensors. In other words, a scene that looks sharp to a human eye may not show anything valuable to a machine vision system.

Available physical space limits an image acquisition system s size, but must accommodate all components. From a camera s viewpoint, direct lighting sources must reside far enough away from an object to evenly illuminate it.