Merging CCTV images can help catch suspects

London, Sept. 23: Combining multiple poor quality CCTV images into a single, computer- enhanced composite could improve the accuracy of facial recognition systems used to identify criminal suspects, a study has found.

Researchers from the University of New South Wales in Australia and University of York in the UK created a series of pictures using a ‘ face averaging’ technique — a method which digitally combines multiple images into a single enhanced image, removing variants such as head angles or lighting so that only features that indicate the identity of the person remain.

They compared how effectively humans and computer facial recognition systems could identify people from high quality images, pixelated images, and face averages.

The results showed that both people and computer systems were better at identifying a face when viewing an average image that combined multiple pixelated images, compared to the original poorquality images.

Computer systems benefited from averaging together multiple images that were already high in quality, and in some cases reached 100 per cent accurate face recognition.

The results have implications for law enforcement and security agencies, where low quality, pixelated images are often the only pictures of suspects available to use in investigations.

The image averaging method offers a standardised way of using images captured from multiple CCTV cameras to create a digital snapshot which can be better recognised by both people and computer software systems.

“We know that not all CCTV systems have the luxury of high quality cameras, meaning that face identifications are often being made from poor quality images,” said Kay Ritchie, from the University of Lincoln in the UK.

“We have shown that there is a relatively quick and easy way to improve pixelated images of someone’s face,” said Ritchie. “We also know anecdotally that there are lots of different techniques that people can use as investigative tools to improve low- quality images, such as manipulating brightness,” she said.

“Our standardised face averaging method could help in suspect identification from low- quality CCTV footage where images from multiple different cameras are available, for example, from tracking a suspect along a particular route,” she added.