Conference proceeding
Watermark Image Restoration Method Based on Block Hopfield Network
ADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 3, PROCEEDINGS, v 5553(3), pp 365-370
01 Jan 2009
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
In this paper, Hopfield network is introduced\ for the restoration of extracted watermark image which may be blurred due to file signal transfer or various signal processing operations. A novel codebook method is designed to reduce the storage space of the network and to increase the security. First, each watermark image is divided into adjacent and non-overlapped sub-block images and mapped into a codebook. Second, this codebook is encrypted by a chaotic sequence. During the process of watermark restoration, the codebook call be obtained via it secret key which is then Used to construct block weight matrix of the neural network for the restoration of the blurred watermark images. Simulation results demonstrate the excellent performance of the proposed method.
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1 citations in Scopus
Details
- Title
- Watermark Image Restoration Method Based on Block Hopfield Network
- Creators
- Xiaohong Ma - Dalian University of TechnologyXin Li - Dalian University of TechnologyHualou Liang - Drexel University
- Contributors
- W Yu (Editor)H B He (Editor)N Zhang (Editor)
- Publication Details
- ADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 3, PROCEEDINGS, v 5553(3), pp 365-370
- Series
- Lecture Notes in Computer Science
- Publisher
- Springer Nature
- Number of pages
- 2
- Grant note
- 60575011 / National Natural Science Foundation of China; National Natural Science Foundation of China (NSFC) 20052181 / Liaoning Province Natural Science Foundation of China; Natural Science Foundation of Liaoning Province
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000268029200039
- Scopus ID
- 2-s2.0-69849088708
- Other Identifier
- 991019170582004721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Theory & Methods