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Creation  Volume 29Issue 3 Cover

Creation 29(3):49
June 2007

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Creation  Volume 29 Issue 3 Cover

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Creation
29(3):49
June 2007

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Surveillance solution: mimicking a bug’s eye view

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Traditional cameras use a single average light setting to control brightness of an image. That works well when there are similar levels of brightness over the whole scene, but not in areas with non-uniform illumination. This is a critical problem for video surveillance cameras, where the clarity of images is crucial for later police identification of suspects.

Images by Dr Russell Brinkworth, The University of Adelaide

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A traditional camera can take a picture that records either the darker indoor subject (top left) or the more brightly illuminated view outside the window (top right), but not both simultaneously. In stark contrast, insect eyes can see both at the same time (bottom left) ‘and keep only the most important bits’ (bottom right) according to physiology researcher Dr Russell Brinkworth. By mimicking how insects see, Dr Brinkworth can now produce digital videos in which ‘you can see every detail’.

A University of Adelaide researcher has been studying insect vision with a view to improving camera technology. ‘When it comes to seeing,’ says Dr Russell Brinkworth, ‘even a tiny insect brain can outperform any current artificial system. As we can, they can see detail in light and dark at the same time.’1

That’s a very useful ability, as Brinkworth says, because ‘even in difficult lighting conditions, such as a person standing in front of a window, you can see both the person’s face and the scenery outside at the same time, something a traditional camera cannot do.’

In an effort to mimic what they’ve observed in insects, Dr Brinkworth and his colleagues have produced new computer software which can be wired into existing digital camera sensor technology.

Just as every surveillance camera is the result of creative intelligence, how much more so are insects’ (and our) eyes, which, as Dr Brinkworth says, ‘can outperform any current artificial system’.

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References

  1. Video cameras learn from insect eyes, The University of Adelaide News & Events, <www.adelaide.edu.au/news/news14341.html>, 21 September 2006.

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