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An R-CNN Based Method to Localize Speech Balloons in Comics

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MultiMedia Modeling (MMM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9516))

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Abstract

Comic books enjoy great popularity around the world. More and more people choose to read comic books on digital devices, especially on mobile ones. However, the screen size of most mobile devices is not big enough to display an entire comic page directly. As a consequence, without any reflow or adaption to the original books, users often find that the texts on comic pages are hard to recognize when reading comics on mobile devices. Given the positions of speech balloons, it becomes quite easy to do further processing on texts to make them easier to read on mobile devices. Because the texts on a comic page often come along with surrounding speech balloons. Therefore, it is important to devise an effective method to localize speech balloons in comics. However, only a few studies have been done in this direction. In this paper, we propose a Regions with Convolutional Neural Network (R-CNN) based method to localize speech balloons in comics. Experimental results have demonstrated that the proposed method can localize the speech balloons in comics effectively and accurately.

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Acknowledgement

This work is supported by National Natural Science Foundation of China (Grant 61300061) and Beijing Natural Science Foundation (4132033).

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Correspondence to Xicheng Liu .

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Wang, Y., Liu, X., Tang, Z. (2016). An R-CNN Based Method to Localize Speech Balloons in Comics. In: Tian, Q., Sebe, N., Qi, GJ., Huet, B., Hong, R., Liu, X. (eds) MultiMedia Modeling. MMM 2016. Lecture Notes in Computer Science(), vol 9516. Springer, Cham. https://doi.org/10.1007/978-3-319-27671-7_37

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  • DOI: https://doi.org/10.1007/978-3-319-27671-7_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27670-0

  • Online ISBN: 978-3-319-27671-7

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