An Introduction to Genetic Algorithms for Scientists and Engineers
An Introduction to Genetic Algorithms for Scientists and Engineers
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
The first 50 years of electronic watermarking
EURASIP Journal on Applied Signal Processing - Emerging applications of multimedia data hiding
Design and analysis of digital watermarking, information embedding, and data hiding systems
Design and analysis of digital watermarking, information embedding, and data hiding systems
A hybrid genetic-neural architecture for stock indexes forecasting
Information Sciences: an International Journal - Special issue: Computational intelligence in economics and finance
Evolutionary Computation: Toward a New Philosophy of Machine Intelligence (IEEE Press Series on Computational Intelligence)
Strategy creation, decomposition and distribution in particle navigation
Information Sciences: an International Journal
Relative risk aversion and wealth dynamics
Information Sciences: an International Journal
Software project management with GAs
Information Sciences: an International Journal
Attacks of simple block ciphers via efficient heuristics
Information Sciences: an International Journal
Information-theoretic analysis of watermarking
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06
Robust watermarking and compression for medical images based on genetic algorithms
Information Sciences: an International Journal
Enhancement of image watermark retrieval based on genetic algorithms
Journal of Visual Communication and Image Representation
IWDW'04 Proceedings of the Third international conference on Digital Watermarking
IEEE Transactions on Information Theory
Information-theoretic analysis of information hiding
IEEE Transactions on Information Theory
Hidden digital watermarks in images
IEEE Transactions on Image Processing
Applying informed coding and embedding to design a robust high-capacity watermark
IEEE Transactions on Image Processing
Optimal watermark detection under quantization in the transform domain
IEEE Transactions on Circuits and Systems for Video Technology
Information Sciences: an International Journal
Data hiding methods based upon DNA sequences
Information Sciences: an International Journal
Rotation invariant watermark embedding based on scale-adapted characteristic regions
Information Sciences: an International Journal
Effective watermarking scheme in the encrypted domain for buyer-seller watermarking protocol
Information Sciences: an International Journal
Information Sciences: an International Journal
Perceptually adaptive spread transform image watermarking scheme using Hadamard transform
Information Sciences: an International Journal
An optimal image watermarking approach based on a multi-objective genetic algorithm
Information Sciences: an International Journal
Watermarking and authentication of quantum images based on restricted geometric transformations
Information Sciences: an International Journal
Adjustable prediction-based reversible data hiding
Digital Signal Processing
Audio watermarking scheme robust against desynchronization attacks based on kernel clustering
Multimedia Tools and Applications
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Watermarking performance enhancement has always been a difficult task since the performance metrics of watermarking systems, i.e., fidelity, robustness, and payload size, inherently conflict with each other. Nowadays, most watermarking schemes hide payloads according to predefined rules or empirical perceptual models. Therefore, the performance of digital watermarking schemes can be determined only passively. In this study, a genetic algorithm-based framework for watermarking performance enhancement is proposed. Watermarked results having better robustness, guaranteed fidelity, and fixed payload size can be obtained. Existing blind-detection watermarking schemes can be improved significantly by incorporating the proposed framework. In addition, the proposed framework has many desirable advantages such as asymmetric embedding/detection overhead, easy integration with existing data-hiding schemes, and direct control over fidelity and robustness.