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23 September, 2021

How to avoid machine vision’s blind spots

11 April, 2013

Appropriate product presentation can also simplify image acquisition and processing. For example, if bottles on a line are all oriented with their labels in the same direction, a single camera may be adequate. If the labels are presented in a random orientation, three or four cameras may be needed to ensure that an image of the full label is available. Similarly, precise product fixturing can simplify and increase inspection accuracy.

In general, time spent optimising the image before the acquisition stage will be repaid many times over during the life of the project, in terms of software development, inspection robustness, and system maintenance requirements.

Image requirements

One of the key factors in determining the architecture of an automated vision system is the pixel resolution needed to achieve the required inspection functions. In industrial applications, the tightest measured tolerance must typically represent 5 to 10 pixels of the acquired image. So a tolerance of ±0.5mm may require a pixel resolution of 100µm. In addition, any feature to be detected must occupy several pixels; single-pixel features are prone to noise and “edge effects” and cannot be detected reliably.

A good rule-of-thumb is that a feature should be 3x3 pixels for detection, so a resolution of around 150µm is needed to detect features 0.5mm in size. Some special processing tools also have their own requirements. Optical character recognition tools typically need individual characters to be 20 to 30 pixels high, for example, so a 12-point typeface would require a resolution of around 200µm.

Once the resolution is known, it is possible to define the camera and lens combination that will allow this to be achieved over the object to be inspected. Difficulties arise when this leads to very large image requirements. For instance, a 1.5m-wide web may contain visible defects that are 250µm across, so 18,000 pixels are needed to span the width of the web. This equates to a typical image size of more than 200 Megapixels – beyond the capabilities of current industrial camera technology. The solution here is to use several cameras, custom optics and software to select areas of interest, or to use linescan or contact image sensor (CIS) technologies.

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