Copyright Protection of Line Drawings:Copyrighted Part Detection Using Cascade Classifiers
Language
English
Type
Proceedings of International Conferences
Authors
Weihan Sun, Koichi Kise
Title
Copyright Protection of Line Drawings:Copyrighted Part Detection Using Cascade Classifiers
Journal
Proceedings of the 2nd China-Japan-Korea Joint Workshop on Pattern Recognition (CJKPR2010)
Pages
pp.9-10
Reviewed
Reviewed
Date
November 2010
Research fields
Pattern recognition
Key
Sun2010_CJKPR (id=1182)
Abstract
To protect the copyright of line drawings, we proposed an image retrieval method to detect both printed
and handwritten partial copies. However, the enormous volumes of line drawing publications with copyright
cause the problem of scalability. Since not the whole image requires copyright protection, a practical method
should detect the copyrighted parts only. In this paper, we propose applying object detection technique to detect
copyrighted parts. By using cascade classifiers, we achieved the detection of comic characters’ faces, which are
important copyrighted parts of line drawing publications. The experimental results show the effectiveness of this
method.
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