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Knowledge-driven understanding of images in comic books

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International Journal on Document Analysis and Recognition (IJDAR) Aims and scope Submit manuscript

Abstract

Document analysis is an active field of research, which can attain a complete understanding of the semantics of a given document. One example of the document understanding process is enabling a computer to identify the key elements of a comic book story and arrange them according to a predefined domain knowledge. In this study, we propose a knowledge-driven system that can interact with bottom-up and top-down information to progressively understand the content of a document. We model the comic book’s and the image processing domains knowledge for information consistency analysis. In addition, different image processing methods are improved or developed to extract panels, balloons, tails, texts, comic characters and their semantic relations in an unsupervised way.

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Notes

  1. In the rest of the paper, “character” is used in the sense of actor or protagonist of a comic’s story, not as a piece of text.

  2. https://github.com/crigaud/publication/tree/master/2015/IJDAR/.

  3. http://digitalcomicmuseum.com.

  4. http://ebdtheque.univ-lr.fr/database/.

  5. http://ebdtheque.univ-lr.fr/database/?overview=1.

  6. http://ebdtheque.univ-lr.fr/references/.

  7. https://code.google.com/p/tesseract-ocr/downloads/list.

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Acknowledgments

The authors would like to thank Karell Bertet and Arnaud Revel for their help with the high-level processing. This work was supported by a European Doctorate scholarship of the University of La Rochelle, European Regional Development Fund, the region Poitou-Charentes (France), the General Council of Charente Maritime (France), the municipality of La Rochelle (France) and the Spanish research projects TIN2011-24631, RYC-2009-05031. We are grateful to all authors and publishers of comics and manga from the eBDtheque dataset for having allowed us to show (Figs. 1–24), use and share their works.

Conflict of interest

The authors declare that there is no conflict of interests. This article does not contain any studies with human or animal subjects.

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Authors and Affiliations

  1. Laboratoire L3i, Université de La Rochelle, 17042, La Rochelle Cedex 1, France

    Christophe Rigaud, Clément Guérin, Jean-Christophe Burie & Jean-Marc Ogier

  2. Computer Vision Center, Universitat Autònoma de Barcelona, 08193, Bellaterra (Barcelona), Spain

    Christophe Rigaud & Dimosthenis Karatzas

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  1. Christophe Rigaud
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  2. Clément Guérin
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  3. Dimosthenis Karatzas
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  4. Jean-Christophe Burie
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  5. Jean-Marc Ogier
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Correspondence to Christophe Rigaud.

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Rigaud, C., Guérin, C., Karatzas, D. et al. Knowledge-driven understanding of images in comic books. IJDAR 18, 199–221 (2015). https://doi.org/10.1007/s10032-015-0243-1

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