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A Comic Retrieval System Based on Multilayer Graph Representation and Graph Mining

  • Thanh-Nam LeEmail author
  • Muhammad Muzzamil Luqman
  • Jean-Christophe Burie
  • Jean-Marc Ogier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9069)

Abstract

Comics analysis offers a lot of interesting Content-based Image Retrieval (CBIR) applications focusing in this special type of document images. In this paper, we propose a scheme to represent and to retrieve comic-page images using attributed Region Adjacency Graphs (RAGs) and their frequent subgraphs. We first extract the graphical structures and local features of each panel in the whole comic volume, then separate different categories of local features to different layers of attributed RAGs. After that, a list of frequent subgraphs is obtained using Frequent Subgraph Mining (FSM) techniques. For CBIR purpose, the recognition and ranking are done by checking for isomorphism between the graphs representing the query image versus the list of discovered frequent subgraphs. Our experimental results show that the proposed approach can achieve reliable retrieval results for comic images browsing using query-by-example (QBE) model.

Keywords

Comics Attributed region adjacency graph Spatial relation Structural pattern recognition CBIR Query-by-example 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Thanh-Nam Le
    • 1
    Email author
  • Muhammad Muzzamil Luqman
    • 1
  • Jean-Christophe Burie
    • 1
  • Jean-Marc Ogier
    • 1
  1. 1.L3i LaboratoryUniversity of La RochelleLa Rochelle Cedex 1France

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