A fast interest point detection algorithm - Chavez, Aaron J (Kansas State University, 2008)
An interest point detection scheme is presented that is comparable in quality to existing methods, but can be performed much faster. The detection is based on a straightforward color analysis at a coarse granularity. A 3x3 grid of squares is centered on the candidate point, so that the candidate point corresponds to the middle square. If the color of the center region is inhomogeneous with all of the surrounding regions, the point is labeled as interesting. A point will also be labeled as interesting if a minority of the surrounding squares are homogeneous, and arranged in an appropriate pattern. Testing confirms that this detection scheme is much faster than the state-of-the-art. It is also repeatable, even under different viewing conditions. The detector is robust with respect to changes in viewpoint, lighting, zoom, and to a certain extent, rotation.
Keywords: Machine vision; Computer Science (0984)