Many applications require detection of multiple features that locally remain consistent in shape and intensity characteristics, but may globally change position with respect to one another over time or under different circumstances. We refer to these feature sets, defined by their characteristic relative positioning, as multifeature constellations. We introduce a method of processing in which multiple levels of correlation, using specially designed composite feature detection filters, are used to first detect local features, and then to detect constellations of these local features. We include experimental procedures and results indicating how the use of multifeature constellation detection may be utilized in applications such as sign language recognition and fingerprint matching.
© 2011 Optical Society of America
Original Manuscript: September 7, 2010
Revised Manuscript: January 31, 2011
Manuscript Accepted: February 22, 2011
Published: April 12, 2011
Charles Casey, Laurence G. Hassebrook, Eli Crane, and Aaron Davidson, "Multifeature distortion-insensitive constellation detection," Appl. Opt. 50, 1650-1659 (2011)