Wavelet neural network based waternarking technology of 2D vector maps

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 has higher robustness,better invisibility and less loss on precision.