Abstract
Comics and manga are one of the most popular and familiar forms of graphic content over the world and play a major role in spreading country’s culture. Nowadays, massive digitization and digital-born materials allow page-per-page mobile reading but we believe that other usages may be released in the near future. In this paper, we focus on speech balloon segmentation which is a key issue for text/graphic association in scanned and digital-born comic book images. Speech balloons are at the interface between text and comic characters, they inform the reader about speech tone and the position of the speakers. We present a generic and text-independent speech balloon segmentation method based on color, shape and topological organization of the connected-components. The method has been evaluated at pixel-level on two public datasets (eBDtheque and Manga109) and the F-measure results are 78.24% and 80.04% respectively.
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Milton Griepp’s White Paper, ICv2 Conference 2014.
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Acknowledgment
This work was supported by the University of La Rochelle (France), the town of La Rochelle and the PIA-iiBD (“Programme d’Investissements d’Avenir”). We are grateful to all authors and publishers of comics and manga images from eBDtheque and Manga109 datasets for allowing us to use their works.
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Rigaud, C., Burie, JC., Ogier, JM. (2017). Text-Independent Speech Balloon Segmentation for Comics and Manga. In: Lamiroy, B., Dueire Lins, R. (eds) Graphic Recognition. Current Trends and Challenges. GREC 2015. Lecture Notes in Computer Science(), vol 9657. Springer, Cham. https://doi.org/10.1007/978-3-319-52159-6_10
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