Content Recapture Detection Based on Convolutional Neural Networks

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Detecting recaptured images has been considered as an important issue. The previous techniques tried to make hand-crafted features represent the statistical characteristics of the recaptured images. Different to the existing methods, the proposed method solves the recapturing detection problem based on a deep learning technique which shows high performance for various applications in recent image processing. Specifically, we propose a recaptured image classification scheme based on a convolutional neural networks (CNNs). To our best knowledge, this is the first work of applying CNNs into the recaptured image detection. For reliable performance evaltuation, we used high-quality database for training and testing. The experimental results show high performance compared to the state-of-the-art methods.
Publisher
SPRINGER VERLAG
Issue Date
2017-03-21
Language
English
Citation

iCatse International Conference on Information Science and Applications (ICISA), pp.339 - 346

ISSN
1876-1100
DOI
10.1007/978-981-10-4154-9_40
URI
http://hdl.handle.net/10203/222506
Appears in Collection
CS-Conference Papers(학술회의논문)
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