Asteroid detection is a topic of great interest due to the possibility of diverting possibly dangerous asteroids or
mining potentially lucrative ones. Currently, asteroid detection is generally performed by taking multiple images of
the same patch of sky separated by 10-15 minutes, then subtracting the images to find movement. However, this is
time consuming because of the need to revisit the same area multiple times per night. This paper describes an
algorithm that can detect asteroids using a single CCD camera scan, thus cutting down on the time and cost of an
asteroid survey. The algorithm is based on the fact that some telescopes scan the sky at multiple wavelengths with a
small time separation between the wavelength components. As a result, an object moving with sufficient speed will
appear in different places in different wavelength components of the same image. Using image processing
techniques we detect the centroids of points of light in the first component and compare these positions to the
centroids in the other components using a nearest neighbor algorithm. The algorithm was used on a test set of 49
images obtained from the Sloan telescope in New Mexico and found 100% of known asteroids with only 3 false
positives. This algorithm has the advantage of decreasing the amount of time required to perform an asteroid scan,
thus allowing more sky to be scanned in the same amount of time or freeing a telescope for other pursuits.
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