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Proceedings Paper

Automatic comic page image understanding based on edge segment analysis
Author(s): Dong Liu; Yongtao Wang; Zhi Tang; Luyuan Li; Liangcai Gao
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Paper Abstract

Comic page image understanding aims to analyse the layout of the comic page images by detecting the storyboards and identifying the reading order automatically. It is the key technique to produce the digital comic documents suitable for reading on mobile devices. In this paper, we propose a novel comic page image understanding method based on edge segment analysis. First, we propose an efficient edge point chaining method to extract Canny edge segments (i.e., contiguous chains of Canny edge points) from the input comic page image; second, we propose a top-down scheme to detect line segments within each obtained edge segment; third, we develop a novel method to detect the storyboards by selecting the border lines and further identify the reading order of these storyboards. The proposed method is performed on a data set consisting of 2000 comic page images from ten printed comic series. The experimental results demonstrate that the proposed method achieves satisfactory results on different comics and outperforms the existing methods.

Paper Details

Date Published: 24 March 2014
PDF: 12 pages
Proc. SPIE 9021, Document Recognition and Retrieval XXI, 90210J (24 March 2014); doi: 10.1117/12.2042521
Show Author Affiliations
Dong Liu, Peking Univ. (China)
Yongtao Wang, Peking Univ. (China)
Zhi Tang, Peking Univ. (China)
Luyuan Li, Peking Univ. (China)
Liangcai Gao, Peking Univ. (China)


Published in SPIE Proceedings Vol. 9021:
Document Recognition and Retrieval XXI
Bertrand Coüasnon; Eric K. Ringger, Editor(s)

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