A fast interest point detection algorithm
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.
School:Kansas State University
School Location:USA - Kansas
Source Type:Master's Thesis
Keywords:machine vision computer science 0984
Date of Publication:01/01/2008