Abstract
Manga, a Japanese word for comics, is a worldwide popular visual entertainment. Nowadays, electronic devices boost the fast development of motion manga for the purpose of visual richness and manga promotion. To convert static manga images into motion mangas, text balloons are usually animated individually for better story telling. This needs the artists to cut out each text balloon meticulously, and therefore it is quite labor-intensive and time-consuming. In this paper, we propose an automatic approach that can extract text balloons from manga images both accurately and effectively. Our approach starts by extracting white areas that contain texts as text blobs. Different from existing text blob extraction methods that only rely on shape properties, we incorporate text properties in order to differentiate text blobs from texture blobs. Instead of heuristic parameter thresholding, we achieve text blob classification via learning-based classifiers. Along with the novel text blob classification method, we also make the first attempt in trying to tackle the boundary issue in balloon extraction. We apply our method on various styles of mangas and comics with texts in different languages, and convincing results are obtained in all cases.
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This project is supported by NSFC (Project No. 61272293), Shenzhen Basic Research Project (Project No. JCYJ20120619152326448), Shenzhen Nanshan Innovative Institution Establishment Fund (Project No. KC2013ZDZJ0007A), the Research Grants Council of the Hong Kong Special Administrative Region, under RGC General Research Fund (Project No. CUHK 417913), NSFC (Project No. 61103120), and Guangzhou Novo Program of Science and Technology (Project No. 0501-330).
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Liu, X., Li, C., Zhu, H. et al. Text-aware balloon extraction from manga. Vis Comput 32, 501–511 (2016). https://doi.org/10.1007/s00371-015-1084-0
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DOI: https://doi.org/10.1007/s00371-015-1084-0