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Citations Publications citing this paper. New color image encryption algorithm based on compound chaos mapping and hyperchaotic cellular neural network Jinqing Li , Fengming Bai , Xiaoqiang Di. References Publications referenced by this paper. High capacity reversible image authentication based on difference image watermarking Yixin Yan , Wei Cao , Shengming Li.
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Adaptive watermark mechanism for rightful ownership protection C. Chang , Pei-Yu Lin.
One-way hash function based on hyper-chaotic cellular neural network Yang Qun-ting , Gao Tiegang. A watermarking-based image ownership and tampering authentication scheme C. A public key watermark for image verification and authentication Ping Wah Wong. International Journal of Computer Applications 61 4 , January Full text available. Multimedia has recently played an increasingly important role in various domains, including Web applications, movies, video game and medical visualization.
Oblivious Neural Network Computing via Homomorphic Encryption
The rapid growth of digital media data over the Internet, on the other hand, makes it easy for anyone to access, copy, edit and distribute digital contents such as electronic documents, images, sounds and videos. Motivated by this, much research work has been dedicated to develop methods for digital data copyright protection, tracing the ownership, and preventing illegal duplication or tampering.
This paper introduces a methodology of robust digital watermarking based on a well-known spherical wavelet transformation, applied to 3D compressed model based on polygonal representation using a neural network. It will be demonstrated in this work that applying a watermarking algorithm on a compressed domain of a 3D object is more effective, efficient, and robust than when applied on a normal domain.
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Taj-eddin and Khalaf F. Abstract Multimedia has recently played an increasingly important role in various domains, including Web applications, movies, video game and medical visualization. References Alexa, M.
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- Robust Digital Watermarking for Compressed 3D Models based on Polygonal Representation.
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