Edit distance for ordered vector sets: A case of study

Abstract

Digital contours in a binary image can be described as an ordered vector set. In this paper an extension of the string edit distance is defined for its computation between a pair of ordered sets of vectors. This way, the differences between shapes can be computed in terms of editing costs. In order to achieve efficency a dominant point detection algorithm should be applied, removing redundant data before coding shapes into vectors. This edit distance can be used in nearest neighbour classification tasks. The advantages of this method applied to isolated handwritten character classification are shown, compared to similar methods based on string or tree representations of the binary image. © Springer-Verlag Berlin Heidelberg 2006.