TY - GEN
T1 - Key generation for static visual watermarking by machine learning
AU - Naoe, Kensuke
AU - Sasaki, Hideyasu
AU - Takefuji, Yoshiyasu
PY - 2009/11/10
Y1 - 2009/11/10
N2 - 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.
AB - 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.
KW - Copyright protection
KW - Digital watermarking
KW - Key generation
KW - Machine learning
KW - Neural network
UR - http://www.scopus.com/inward/record.url?scp=70350704842&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70350704842&partnerID=8YFLogxK
U2 - 10.1109/ICMLC.2009.5212624
DO - 10.1109/ICMLC.2009.5212624
M3 - Conference contribution
AN - SCOPUS:70350704842
SN - 9781424437030
T3 - Proceedings of the 2009 International Conference on Machine Learning and Cybernetics
SP - 3089
EP - 3094
BT - Proceedings of the 2009 International Conference on Machine Learning and Cybernetics
T2 - 2009 International Conference on Machine Learning and Cybernetics
Y2 - 12 July 2009 through 15 July 2009
ER -