On the Detection of Dominant Points on Digital Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simple fast algorithms for the editing distance between trees and related problems
SIAM Journal on Computing
A note on the Nagendraprasad-Wang-Gupta thinning algorithm
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
The String-to-String Correction Problem
Journal of the ACM (JACM)
Comparison of AESA and LAESA search algorithms using string and tree-edit-distances
Pattern Recognition Letters
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
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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.