Automatic comic page image understanding based on edge segment analysis

Dong Liu; Yongtao Wang; Zhi Tang; Luyuan Li; Liangcai Gao

doi:10.1117/12.2042521

24 March 2014 Automatic comic page image understanding based on edge segment analysis

Dong Liu, Yongtao Wang, Zhi Tang, Luyuan Li, Liangcai Gao

Proceedings Volume 9021, Document Recognition and Retrieval XXI; 90210J (2014) https://doi.org/10.1117/12.2042521
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States

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.

Citation Download Citation

Dong Liu, Yongtao Wang, Zhi Tang, Luyuan Li, and Liangcai Gao "Automatic comic page image understanding based on edge segment analysis", Proc. SPIE 9021, Document Recognition and Retrieval XXI, 90210J (24 March 2014); https://doi.org/10.1117/12.2042521

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