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A Novel Graph Database for Handwritten Word Images

  • Michael Stauffer
  • Andreas Fischer
  • Kaspar Riesen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10029)

Abstract

For several decades graphs act as a powerful and flexible representation formalism in pattern recognition and related fields. For instance, graphs have been employed for specific tasks in image and video analysis, bioinformatics, or network analysis. Yet, graphs are only rarely used when it comes to handwriting recognition. One possible reason for this observation might be the increased complexity of many algorithmic procedures that take graphs, rather than feature vectors, as their input. However, with the rise of efficient graph kernels and fast approximative graph matching algorithms, graph-based handwriting representation could become a versatile alternative to traditional methods. This paper aims at making a seminal step towards promoting graphs in the field of handwriting recognition. In particular, we introduce a set of six different graph formalisms that can be employed to represent handwritten word images. The different graph representations for words, are analysed in a classification experiment (using a distance based classifier). The results of this word classifier provide a benchmark for further investigations.

Keywords

Graph benchmarking dataset Graph repository Graph representation for handwritten words 

Notes

Acknowledgments

This work has been supported by the Hasler Foundation Switzerland.

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Michael Stauffer
    • 1
    • 3
  • Andreas Fischer
    • 2
  • Kaspar Riesen
    • 1
  1. 1.Institute for Information SystemsUniversity of Applied Sciences and Arts Northwestern SwitzerlandOltenSwitzerland
  2. 2.University of Fribourg and HES-SOFribourgSwitzerland
  3. 3.Department of InformaticsUniversity of PretoriaPretoriaSouth Africa

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