Modelling the Generalised Median Correspondence Through an Edit Distance

  • Carlos Francisco Moreno-García
  • Francesc Serratosa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11004)


On the one hand, classification applications modelled by structural pattern recognition, in which elements are represented as strings, trees or graphs, have been used for the last thirty years. In these models, structural distances are modelled as the correspondence (also called matching or labelling) between all the local elements (for instance nodes or edges) that generates the minimum sum of local distances. On the other hand, the generalised median is a well-known concept used to obtain a reliable prototype of data such as strings, graphs and data clusters. Recently, the structural distance and the generalised median has been put together to define a generalise median of matchings to solve some classification and learning applications. In this paper, we present an improvement in which the Correspondence edit distance is used instead of the classical Hamming distance. Experimental validation shows that the new approach obtains better results in reasonable runtime compared to other median calculation strategies.


Generalised median Edit distance Optimisation Weighted mean 



This research is supported by the Spanish projects TIN2016-77836-C2-1-R, ColRobTransp MINECO DPI2016-78957-R AEI/FEDER EU and the European project AEROARMS, H2020-ICT-2014-1-644271.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Carlos Francisco Moreno-García
    • 1
  • Francesc Serratosa
    • 2
  1. 1.The Robert Gordon UniversityAberdeenScotland, UK
  2. 2.Universitat Rovira i VirgiliTarragonaSpain

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