Comic2CEBX: A system for automatic comic content adaptation

Abstract

Comics are popular almost throughout the world. With the help of comic document digitization, it is much easier for people to archive and browse comic works. However, there are still some big challenges along with comic document digitization progress. Among these challenges, comic content adaptation is an important one to be tackled. The existing works only focus on parts of this problem and do not provide a tangible solution to display comic contents on different devices. In this paper, we solve these problems by proposing Comic2CEBX, a system which can automatically convert a set of scanned comic page images into a CEBX file that allows reflowing of the original comic pages with fixed layouts. Taking raw comic images as inputs, our system first extracts three kinds of low-level visual patterns and then uses multilayer Conditional Random Fields to detect all the panels. Meanwhile, our system automatically identifies the reading orders of the panels within each page. Finally, we encapsulate the comic page images and the obtained page structure information (i.e., the panels detection results and the corresponding reading orders) to generate a CEBX file. Experimental results show that our comic page layout analysis method achieves better performance than the existing ones, and use case presentation of the CEBX files produced by our system demonstrates that it brings better comic reading experience especially on mobile devices.