(auto): Fast Geometric Hashing for Automated Astrometry is a fascinating presentation about a solution to the problem of examining a photo of a section of the sky, and figuring out what part of the sky it is. It involves geometry, and algorithms, a clever hashing algorithm for that returns the same result independent of rotation and scale, mapping, search trees, and so on.

Fast geometric hashing for automated astrometry

Friday 20 February 2009This is over 16 years old. Be careful.

Fast Geometric Hashing for Automated Astrometry is a fascinating presentation about a solution to the problem of examining a photo of a section of the sky, and figuring out what part of the sky it is. It involves geometry, and algorithms, a clever hashing algorithm for that returns the same result independent of rotation and scale, mapping, search trees, and so on.

I’m not much of an astronomer: I didn’t realize for example, that the catalog of the sky included roughly a billion objects! I’d never heard of HEALPix, a scheme for dividing spheres into uniform grids (pixelizing them). And kd-trees are a data structure for dividing up space, kind of like a 3D tree map.

Plenty of goodies for nerds of all sorts.

PS: the whole thing has been hooked up with the flickr API to automatically identify objects in astronomy pictures on flickr. Very cool.

Comments

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Ned, thanks for this great link! I was staring at a photograph of the sky recently that I had taken somewhere out West, and after several minutes gave up trying to figure out which patch of sky it was. Now I know where to go to find a match.

I guess I can't really incorporate this into PyEphem because it doesn't do image processing. Too bad. :-)

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