Astrobiologists are overwhelmed by the huge volume of images from other planets. Now they have help in the form of a system that automatically identifies objects of interest in geological images

The search for life on other planets is hotting up. The seemingly endless train of Mars rovers have found convincing evidence of a warmer and wetter climate on Mars. The Huygens and Cassini spacecraft have found lakes, beaches, rivers and rain on Titan (albeit of the the oily variety). And Europas dark, warm ocean looks increasingly inviting for astrobiologists.

Then there are the ever-increasing hordes of exoplanets in the habitable zones around other stars.Its never been a better time to be an astrobiologist.

One problem that this new breed of scientist faces is data overload. Each image from Mars has to be pored over by a human expert before the rovers next move can be planned and executed.

And since these images are increasingly numerous, this is a time consuming task. So a way to automate the classification of these images, at least partially, would be hugely useful.

Step forward Patrick McGuire at the Freie Universitt in Berlin, Germany and a few pals who have built and tested an automated system that does just this. They call their new system the cyborg astrobiologist.

The new system is relatively simple. It consists of a Samsung Propel smartphone, which has a camera capable of taking 1280 x 960 pixel images, connected by bluetooth to a Dell Inspiron 9300 laptop. For the moment, it requires a human helper to carry and point the camera but its not hard to imagine how the system could be fitted to an autonomous rover.

The phone takes photos of the terrain as it moves around, sending them it to the laptop for analysis. This where the clever part takes place.

The laptop analyses each photo by comparing it earlier images it has received and looking for similarities between them. It analyses the colour of the scene and the texture to calculate a similarity score.

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