A distance measure for structural descriptions using circular arcs as primitives

This paper proposes a structural description scheme using circular arcs as primitives. On this scheme, a metric for defining a distance between pairs of circular arcs and relations among them, is introduced and its main properties are discussed. This metric is based on a set of perceptive criteria which allow to increase its effectiveness in application domains characterized by high variability in the shape of the visual patterns. The whole approach is general enough to be satisfactorily used in a wide class of applications. The metric has been validated by employing it in a nearest neighbour classifier, which has been used for automatic recognition of handwritten digits extracted from a standard character database.

[1]  Esther M. Arkin,et al.  An efficiently computable metric for comparing polygonal shapes , 1991, SODA '90.

[2]  Mario Vento,et al.  A neural network classifier for OCR using structural descriptions , 1995 .

[3]  JOHN F. Young Machine Intelligence , 1971, Nature.

[4]  Theodosios Pavlidis,et al.  A shape analysis model with applications to a character recognition system , 1992, [1992] Proceedings IEEE Workshop on Applications of Computer Vision.

[5]  King-Sun Fu,et al.  A graph distance measure for image analysis , 1984, IEEE Transactions on Systems, Man, and Cybernetics.

[6]  King-Sun Fu,et al.  An Image Understanding System Using Attributed Symbolic Representation and Inexact Graph-Matching , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Theodosios Pavlidis,et al.  A Shape Analysis Model with Applications to a Character Recognition System , 1994, IEEE Trans. Pattern Anal. Mach. Intell..