Subgraph spotting in graph representations of comic book images
Le, TN; Luqman, MM; Dutta, A; et al.Héroux, P; Rigaud, C; Guérin, C; Foggia, P; Burie, JC; Ogier, JM; Lladós, J; Adam, S
Date: 20 June 2018
Journal
Pattern Recognition Letters
Publisher
Elsevier
Publisher DOI
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 ...
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.
Computer Science
Faculty of Environment, Science and Economy
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Except where otherwise noted, this item's licence is described as © 2018. This version is made available under the CC-BY-NC-ND 4.0 license: https://creativecommons.org/licenses/by-nc-nd/4.0/
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