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How to avoid machine vision’s blind spots

11 April, 2013

In one recent project, my company supplied an array of eight 8-Megapixel cameras integrated with an advanced datalogging system to measure the contents of 96 well assay trays for a pharmaceutical business. The resulting high-resolution images were processed on several PCs enabling inspection at high production speeds.

Linear speed

The linear speed of moving products and the cycle time available for inspection also play a key role in determining the camera hardware and processing capabilities required to deliver a working system.

If a product is moving continuously, then the acquisition must freeze the movement to avoid motion blur in the image. This can be done using either short exposure times or strobe lighting. In both cases, intense light is needed, and specialised sources are often used to achieve an adequately bright image. With “standard” cameras, it is feasible to operate at exposures of around 0.1ms. For example, a resolution of 5µm and a close-up image 8mm wide would allow a linear speed of around 50mm/s before discernible blurring occurred. Specialised high-speed cameras can offer dramatically faster acquisition.

Once the sensor has been exposed, the data must be transferred from the camera to the processor. In general, high-resolution cameras have lower maximum frame rates, and this is also affected by the data transfer interface. Five to 100 frames per second are typical in the field. Recently, several high-speed camera interfaces have become available, including CameraLink and the more recent coaXpress standard.

The acquired images then have to be processed and analysed. The time taken to achieve this depends on the image content and the algorithms being used. Simple edge-finding or thresholding operations can be executed in sub-millisecond timeframes, even on large images, but advanced pattern recognition, character reading, or blob analysis can extend this by orders of magnitude. Higher speeds and more complex analyses are facilitated by increased processing power, and the most advanced systems use high-powered, intelligent cameras, and multiple, multi-core PCs with image processing distributed across them.

The bigger picture

Finally, whatever the technologies involved, the machine vision system must work smoothly with the organisation’s wider production and quality assurance processes. Getting this right requires attention to a host of factors that cover the full scope of the process. At the work-cell level, the system design should minimise the load on operators, reduce the possibility of errors and be reconfigured easily to accommodate product changeovers.

Across the production process, machine vision activities must integrate with other aspects of automation and quality control, from PLCs to check-weighers and label printers. At the management level, the system must store relevant product data in an accessible and regulatory-compliant manner. In the past, integrating machine vision systems in this way required extensive and labour-intensive custom programming, but today the availability of dedicated integration packages – such as Optimal’s synTI print and inspect system – have greatly simplified, accelerated and reduced the cost of such efforts, ensuring that machine vision is seamlessly integrated into the bigger picture.

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