Key Generation for Static Visual Watermarking by Machine Learning
Digital watermarking became a key technology for protecting copyrights. In this paper, we propose a method of key generation scheme for static visual digital watermarking by using machine learning technology, neural network as its exemplary approach for machine learning method. The proposed method is to provide intelligent mobile collaboration with secure data transactions using machine learning approaches, herein neural network approach as an exemplary technology.First, the proposed method of key generation is to extract certain type of bit patterns as training data set for machine learning of digital watermark. Second, the proposed method of watermark extraction is processed by presenting visual features by the training approach of machine learning technology. Third, the training approach is to converge the extraction key as the classifier, which is generated by the machine learning process is used as watermark extraction key.The proposed method is to contribute to secure visual information hiding without losing any detailed data of visual objects or any additional resources of hiding visual objects as molds to embed hidden visual objects.
Digital Watermarking Machine Learning Key generation Neural Network Copyright Protection
KENSUKE NAOE HIDEYASU SASAKI YOSHIYASU TAKEFUJI
Graduate School of Media and Governance, Keio University 5322 Endoh, Fujisawa, Kanagawa 252-8520, Ja Department of Information Science and Engineering, Ritsumeikan University, 6-4-10 Wakakusa, Kusatsu, Faculty of Environment and Information Studies, Keio University, 5322 Endoh, Fujisawa, Kanagawa 252-
国际会议
2009 International Conference on Machine Learning and Cybernetics(2009机器学习与控制论国际会议)
保定
英文
3089-3094
2009-07-12(万方平台首次上网日期,不代表论文的发表时间)