3D-printed magic lens unscrambles hidden animations

Sandrine Ceurstemont, editor, New Scientist TV

A magic lens can now be used to turn a picture of a landscape into a portrait of President Obama or to watch a crawling worm emerge from a random pattern. Developed by Wojciech Jarosz from Disney Research, Zurich and colleagues, the new system uses a 3D printer to shape a block of clear plastic, creating a lens that can unscramble hidden images or animations.

The technique can produce a generic lens that decodes a range of scrambled images warped using a given set of rules. But it can also create a bespoke unscrambling lens that transforms one picture into another by providing an algorithm with the two images. "The source image can be anything at all," says Jarosz. "As long as it has all the necessary colours or shades of grey that are present in the hidden image."

As seen in the video, the lens is made up of lots of smooth facets with different orientations. Its surface is designed using a computer programme that comes up with the best possible shape based on caustics and the type of decoding required. Since a lens uncovers secret images by exploiting refraction, a facet isn't necessarily uncovering the portion of the image directly underneath.

Jarosz came up with the idea thanks to inspiration from a previous project where an engraved panel was designed to cast images on walls. "I realised that we could try the same idea but in reverse to get another interesting effect," says Jarosz.

The team is now looking at how they can improve image quality by manufacturing lenses using a professional process. The technique could provide a new way of engaging children in museums, or to pass secret messages between cellphones that can only be decoded by viewing the screen through a magic lens. "They could even some day be used as a security measure in bank notes," says Jarosz.

The research will be presented later this month at Siggraph Asia, a leading conference on computer graphics and interactive techniques in Singapore, Malaysia.

If you enjoyed this post, see how you can decode invisible images in signs by waving your hand or watch a handheld camera see through objects.

Source: http://feeds.newscientist.com/c/749/f/10897/s/25e2fe0c/l/0L0Snewscientist0N0Cblogs0Cnstv0C20A120C110C3d0Eprinted0Emagic0Elens0Eunscrambles0Esecret0Eanimations0Bhtml0Dcmpid0FRSS0QNSNS0Q20A120EGLOBAL0Qonline0Enews/story01.htm

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