title: On the orientability of shapes.
abstract: The orientation of a shape is a useful quantity, and has been shown to affect performance of object recognition in the human visual system. Shape orientation has also been used in computer vision to provide a properly oriented frame of reference, which can aid recognition. However, for certain shapes, the standard moment-based method of orientation estimation fails. We introduce as a new shape feature shape orientability, which defines the degree to which a shape has distinct (but not necessarily unique) orientation. A new method is described for measuring shape orientability, and has several desirable properties. In particular, unlike the standard moment-based measure of elongation, it is able to differentiate between the varying levels of orientability of n-fold rotationally symmetric shapes. Moreover, the new orientability measure is simple and efficient to compute (for an n-gon we describe an O(n) algorithm).
authors.affiliation: Computer Science Department, Exeter University, Exeter EX4 4QF, UK. J.Zunic@exeter.ac.uk
authors.forename: Jovisa
authors.initials: J
authors.lastname: Zunić
authors.forename: Paul L
authors.initials: PL
authors.lastname: Rosin
authors.forename: Lazar
authors.initials: L
authors.lastname: Kopanja
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*