Deep Convolutional Neural Networks for Manga Show-Through Cancellation

Taku NAKAHARA  Kazunori URUMA  Tomohiro TAKAHASHI  Toshihiro FURUKAWA  

IEICE TRANSACTIONS on Information and Systems   Vol.E101-D   No.11   pp.2844-2848
Publication Date: 2018/11/01
Publicized: 2018/08/02
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2018EDL8051
Type of Manuscript: LETTER
Category: Image Processing and Video Processing
manga,  image show-through cancellation,  deep convolutional neural network,  residual learning,  batch normalization,  

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Recently, the demand for the digitization of manga is increased. Then, in the case of an old manga where the original pictures have been lost, we have to digitize it from comics. However, the show-through phenomenon would be caused by scanning of the comics since it is represented as the double sided images. This letter proposes the manga show-through cancellation method based on the deep convolutional neural network (CNN). Numerical results show that the effectiveness of the proposed method.