Subgraph spotting in graph representations of comic book images

Thanh Nam Le, Muhammad Muzzamil Luqman, Anjan Dutta, Pierre Héroux, Christophe Rigaud, Clément Guérin, Pasquale Foggia, Jean Christophe Burie, Jean Marc Ogier, Josep Lladós, Sébastien Adam

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)

Abstract

© 2018 Elsevier B.V. Graph-based representations are the most powerful data structures for extracting, representing and preserving the structural information of underlying data. Subgraph spotting is an interesting research problem, especially for studying and investigating the structural information based content-based image retrieval (CBIR) and query by example (QBE) in image databases. In this paper we address the problem of lack of freely available ground-truthed datasets for subgraph spotting and present a new dataset for subgraph spotting in graph representations of comic book images (SSGCI) with its ground-truth and evaluation protocol. Experimental results of two state-of-the-art methods of subgraph spotting are presented on the new SSGCI dataset.
Original languageEnglish
Pages (from-to)118-124
JournalPattern Recognition Letters
Volume112
DOIs
Publication statusPublished - 1 Sep 2018

Keywords

  • Attributed graph
  • Dataset and comic book images
  • Graph indexing
  • Graph isomorphism
  • Graph matching
  • Graph retrieval
  • Query by example
  • Region adjacency graph
  • Subgraph isomorphism
  • Subgraph spotting

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