The software known as AverageExplorer, searches out thousands of images of a given subject, then amalgamates them into one composite ‘average’ image.

Software program was created by a team led by associate professor Alexei Efros.

Users can refine their search criteria either by using more specific terms, or just by selecting a specific region of the average image an example could involve selecting the nose on the average cat image, resulting in a new average image that's weighted more toward matching up noses.

"Visual data is among the biggest of Big Data," said Efros.

"We have this enormous collection of images on the web, but much of it remains unseen by humans because it is so vast. People have called it the dark matter of the internet. We wanted to figure out a way to quickly visualize this data by systematically 'averaging' the images," Efros added.

Additionally, the software could be used to train computer vision systems.

Using AverageExplorer, however, if a feature on an average image is marked, then that feature will also automatically be marked in all of the contributing images.