"We wanted to see whether a machine could answer questions, such as 'Do children resemble their parents' or 'what parts of the face are more genetically inspired'," said lead researcher Afshin Dehfghan from University of Central Florida (UCF).

The new tool is able to focus on indicators people may not find as significant - such as the left eye, the chin and parts of the forehead.

By designing an algorithm to focus on specific features, the research team converted the photos into a checkerboard of patches and extracted tiny snapshots of the most significant facial parts.

The tool compared all the photos feature by feature and sorted them by the most probable match.

The team found that its programme not only did a better job of matching features of parents and their kids than random chance, but it also outperformed existing software for identifying relatives through photos by three to 10 percent.

"As this tool is developed, I could see it being used to identify long-time missing children as they mature," said Ross Wolf, an associate professor of criminal justice at UCF.

(Agencies)

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