A novel lossless information hiding algorithm based on wavelet neural network for digital vector maps is introduced. Wavelet coefficients being manipulated are embedded into a vector map, which could be restored by ad...A novel lossless information hiding algorithm based on wavelet neural network for digital vector maps is introduced. Wavelet coefficients being manipulated are embedded into a vector map, which could be restored by adjusting the weights of neurons in the designed neural network. When extracting the watermark extraction, those coefficients would be extracted by wavelet decomposition. With the trained multilayer feed forward neural network, the watermark would be obtained finally by measuring the weights of neurons. Experimental results show that the average error coding rate is only 6% for the proposed scheme and compared with other classical algorithms on the same tests, it is indicated that the proposed algorithm hashigher robustness, better invisibility and less loss on precision.展开更多
We propose a robust watermarking scheme and several extensions for digital right management of data cubes.The ownership information is hidden into a data cube by modifying a set of selected cell values.Its owner can u...We propose a robust watermarking scheme and several extensions for digital right management of data cubes.The ownership information is hidden into a data cube by modifying a set of selected cell values.Its owner can use his private key to control all the watermarking parameters freely.Neither original data cube nor the watermark is required in watermark detection.Detailed analysis and extensive experiments are conducted for the proposed schemes in terms of watermark detectability,robustness and efficiency.Our results show that the scheme performs well in actual applications.展开更多
文摘A novel lossless information hiding algorithm based on wavelet neural network for digital vector maps is introduced. Wavelet coefficients being manipulated are embedded into a vector map, which could be restored by adjusting the weights of neurons in the designed neural network. When extracting the watermark extraction, those coefficients would be extracted by wavelet decomposition. With the trained multilayer feed forward neural network, the watermark would be obtained finally by measuring the weights of neurons. Experimental results show that the average error coding rate is only 6% for the proposed scheme and compared with other classical algorithms on the same tests, it is indicated that the proposed algorithm hashigher robustness, better invisibility and less loss on precision.
基金the National Natural Science Foundation of China(No.60703032)the National High Technology Research and Development Program(863)of China(No.2007AA01Z456)
文摘We propose a robust watermarking scheme and several extensions for digital right management of data cubes.The ownership information is hidden into a data cube by modifying a set of selected cell values.Its owner can use his private key to control all the watermarking parameters freely.Neither original data cube nor the watermark is required in watermark detection.Detailed analysis and extensive experiments are conducted for the proposed schemes in terms of watermark detectability,robustness and efficiency.Our results show that the scheme performs well in actual applications.
