How do you think the new GigE standards will influence the machine vision industry?
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It's Quality Time
Manufacturers of virtually all products employ some sort of quality inspection in order to verify that their products are functional, safe and in some cases, appealing to the eye. Because of their repeatability, reliability and cost-effectiveness, machine vision systems are used extensively in inspection procedures such as precision measurement, Optical Character Recognition (OCR) and Optical Character Verification (OCV), Data Matrix and Barcode reading, color recognition and part recognition. Virtually anything that can be inspected by the human eye human can be inspected by a machine vision system. However, machine vision systems require a crisp, clear image of the inspected object to which their complex algorithms and routines are applied. The single most important factor in the processing of those images is contrast. For that reason, specialized lighting can be found in the majority of machine vision applications.
The Elements of Lighting
Lighting components are used to control "light delivery" to the camera. There are many lighting configurations to choose from, including ring lights, dark-field and bright-field lights, backlights, coaxial (on axis) lights, continuous diffuse lights, dome lights, area arrays, line lights and spot lights. Application of the different types of lighting is somewhat of an exact science, and this article will provide a few example applications intended to "shed some light" on the importance of lighting in machine vision inspection applications.
As mentioned, contrast is the name of the game. Because light reflects differently on different surfaces, there is no "one-size-fits-all" in machine vision lighting that can create contrast on every item.
As shown in Figure 1, diffuse surfaces, such as wood, paper, plastic and some metals, reflect light in a particular way.
Specular or mirror-like surfaces, such as gear parts, cell phone displays and glass reflect light in a different way (Figure 2).