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  1. International Journal of Document Analysis and Recognition (IJDAR)
  2. International Journal of Document Analysis and Recognition (IJDAR) : Volume 16
  3. International Journal of Document Analysis and Recognition (IJDAR) : Volume 16, Issue 4, December 2013
  4. Detection of exact and similar partial copies for copyright protection of manga
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International Journal of Document Analysis and Recognition (IJDAR) : Volume 20
International Journal of Document Analysis and Recognition (IJDAR) : Volume 19
International Journal of Document Analysis and Recognition (IJDAR) : Volume 18
International Journal of Document Analysis and Recognition (IJDAR) : Volume 17
International Journal of Document Analysis and Recognition (IJDAR) : Volume 16
International Journal of Document Analysis and Recognition (IJDAR) : Volume 16, Issue 4, December 2013
Image search in patents: a review
Detection of exact and similar partial copies for copyright protection of manga
Clutter noise removal in binary document images
Farsi/Arabic handwritten digit recognition based on ensemble of SVD classifiers and reliable multi-phase PSO combination rule
Visual word density-based nonlinear shape normalization method for handwritten Chinese character recognition
Effective technique for the recognition of offline Arabic handwritten words using hidden Markov models
Fast self-generation voting for handwritten Chinese character recognition
International Journal of Document Analysis and Recognition (IJDAR) : Volume 16, Issue 3, September 2013
International Journal of Document Analysis and Recognition (IJDAR) : Volume 16, Issue 2, June 2013
International Journal of Document Analysis and Recognition (IJDAR) : Volume 16, Issue 1, March 2013
International Journal of Document Analysis and Recognition (IJDAR) : Volume 15
International Journal of Document Analysis and Recognition (IJDAR) : Volume 14
International Journal of Document Analysis and Recognition (IJDAR) : Volume 13
International Journal of Document Analysis and Recognition (IJDAR) : Volume 12
International Journal of Document Analysis and Recognition (IJDAR) : Volume 11
International Journal of Document Analysis and Recognition (IJDAR) : Volume 10
International Journal of Document Analysis and Recognition (IJDAR) : Volume 9
International Journal of Document Analysis and Recognition (IJDAR) : Volume 8
International Journal of Document Analysis and Recognition (IJDAR) : Volume 7
International Journal of Document Analysis and Recognition (IJDAR) : Volume 6
International Journal of Document Analysis and Recognition (IJDAR) : Volume 5
International Journal of Document Analysis and Recognition (IJDAR) : Volume 4
International Journal of Document Analysis and Recognition (IJDAR) : Volume 3
International Journal of Document Analysis and Recognition (IJDAR) : Volume 2
International Journal of Document Analysis and Recognition (IJDAR) : Volume 1

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Detection of exact and similar partial copies for copyright protection of manga

Content Provider Springer Nature Link
Author Sun, Weihan Kise, Koichi
Copyright Year 2013
Abstract Manga, a kind of Japanese comic book, is an important genre in the realm of image publications requiring copyright protection. To copy manga, illegal users generally focus on certain interesting parts from which to make partial copies to apply in their own drawings. With respect to their sources, copying of manga can be divided into two types: (1) exact copies, which duplicate specific contents of manga, such as scanned manga publications (printed copies) and traced outlines of manga (hand-drawn copies), and (2) similar partial copies, which infringe the copyright of manga characters based on their features. In this paper, we propose applying content-based image retrieval methods to detect both exact and similar copies based on two kinds of regions of interest (ROIs): generic ROIs and face ROIs. The method is able not only to locate the partial copies from images with complex backgrounds, but also to report the corresponding copied parts of copyrighted manga pages for exact copy detection and copied manga characters for similar copy detection. The experimental results prove high performance of the proposed method for detecting printed partial copies. In addition, 85 % of hand-drawn and 77 % of similar partial copies were detected with relatively high precision using a database containing more than $$10{,}000$$ manga pages.
Starting Page 331
Ending Page 349
Page Count 19
File Format PDF
ISSN 14332833
Journal International Journal of Document Analysis and Recognition (IJDAR)
Volume Number 16
Issue Number 4
e-ISSN 14332825
Language English
Publisher Springer Berlin Heidelberg
Publisher Date 2013-03-01
Publisher Place Berlin, Heidelberg
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Manga Printed copy Hand-drawn copy Similar copy Partial copy Content-based image retrieval Image Processing and Computer Vision Pattern Recognition
Content Type Text
Resource Type Article
Subject Computer Science Applications Computer Vision and Pattern Recognition Software
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