@Article{ThanhNamLe2018,
author="Thanh Nam Le
and Muhammad Muzzamil Luqman
and Anjan Dutta
and Pierre Heroux
and Christophe Rigaud
and Clement Guerin
and Pasquale Foggia
and Jean Christophe Burie
and Jean Marc Ogier
and Josep Llados
and Sebastien Adam",
title="Subgraph spotting in graph representations of comic book images",
journal="Pattern Recognition Letters",
year="2018",
volume="112",
pages="118--124",
optkeywords="Attributed graph",
optkeywords="Region adjacency graph",
optkeywords="Graph matching",
optkeywords="Graph isomorphism",
optkeywords="Subgraph isomorphism",
optkeywords="Subgraph spotting",
optkeywords="Graph indexing",
optkeywords="Graph retrieval",
optkeywords="Query by example",
optkeywords="Dataset and comic book images",
abstract="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.",
optnote="DAG; 600.097; 600.121",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=3150), last updated on Thu, 28 Mar 2019 10:26:45 +0100",
opturl="https://doi.org/10.1016/j.patrec.2018.06.017"
}