When you are developing a color machine vision system, you will have a lot of options to choose from. First of all, you will have to choose between an area scan or line scan color camera. Based on this choice, you will need to choose between a bayer color camera, trilinear camera or prism technology.
This blog is part of a three-part series where we will cover the factors you need to consider when developing a color machine vision system. This blog is the second part that mentions four factors. Be sure to read the other parts where we discuss other factors you’ll need to consider.
Color artifacts
Color artifacts are image defects – often falsely-colored pixels or patterns – caused by the way that the color information for the image is derived. Cameras that use estimation or interpolation to calculate color are most likely to exhibit color artifacts.
However, even trilinear cameras, which produce independent R, G, and B values (non-interpolated), can generate color artifacts due to spatial offsets caused by keystone effects, uneven surfaces, or slight timing variances. Because prism cameras have three individual sensors and use a single optical plane to capture the image, there is a very low risk of generating color artifacts with prism cameras. The most common types of color artifacts are:
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Color aliasing: Color aliasing refers to situations when a line or the edge of an object with a particular color (for example, a dark blue diagonal line) shows different colors, like redish or yellowish pixels along its edges when an image is examined at the pixel level.
This problem is most common with Bayer cameras because the interpolation technique used to assign an RGB value to each pixel uses a mixture of surrounding pixels which may have completely different colors than the line or edge itself.
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Moiré pattern
Besides causing problems when capturing a single edge or line, large-scale aliasing can result in the appearance of a moiré pattern when images contain fine repeating patterns. Although this effect can occur with any camera needing to capture higher spatial frequencies, a Bayer camera is extra prone to this— again because of the interpolation technique.
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Impact on resolution
Compared to a monochrome system, special care is required when determining the level of resolution needed in a color machine vision system. That’s because color technologies like Bayer interpolation greatly reduce the effective resolution of the camera. While a Bayer camera might have five million pixels (5 megapixels), the interpolation process “averages out” many of the small details rendering the effective resolution to somewhere between one-third to one-half of the overall pixel number.
Depending on the minimum feature size that your application must be able to detect/analyze, and the size of the field-of-view that must be covered, there are two possible courses of action:
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You can choose a Bayer camera with a much higher resolution than you might use on a similar monochrome system. Of course, this typically comes with a higher price tag, more expensive optics, and a higher processing load on your host computer.
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You can choose a prism camera with roughly the same base resolution than you would use on a monochrome system. A 3.2-megapixel prism camera is really a 3 x 3.2-megapixel camera with three separate image sensors totaling 9.6 megapixels. Thus it can produce 24-bit, 3.2-megapixel output without the loss of resolution as in Bayer cameras. Prism cameras are, as noted, more expensive than Bayer cameras. But when compared with all the associated costs of using a 9-megapixel Bayer camera, the overall comparison becomes much closer.
The information above applies only to area scan resolution. In the case of line scan systems, neither trilinear nor prism cameras rely on interpolation, so there is no significant reduction in effective resolution for either technology. However, some previously described issues, such as color artifacts and color crosstalk, may affect the ability of a trilinear camera to discriminate small details as precisely as the single optical plane of a prism camera.
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Application examples:
Here are a few application examples where the Sweep Plus Series prism-based cameras are especially suitable:
”Unwrapping” of cylindrical items such as
bottles, cans, pens etc., for 360-degree
label inspection.
Color sorting and quality inspection of jelly bears.
Print inspection of bank notes.
Sorting of lumber by color and grain pattern,
color matching on laminates and other flooring products.
Sorting and quality of carrots, potatoes and
other vegetables.
Sorting and quality inspection and olives
and nuts.
Inspection and separation of valuable mineral
ores from waste rock.
Sorting and inspection in recycling and
waste streams.
Steel metal and coin inspection.