Multiple watermarking for images using back-propagation neural network and DWT

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Abstract

An effective multiple watermarking technique supported on neural network into the wavelet transform can be proposed. The wavelet coefficients has been preferred by Human Visual System. In the proposed work focus on Discrete Wavelet Transform based segmented image watermarking techniques using Back-Propagation neural networks. Using improved BPNN, the multiple watermarks are embedded into the original image, which can advance the pace of the learn, reduce the error and the qualified neural networks are extricate multiple watermarks as of the embedded images. The planned strategy achieves a excellent visual effect scheduled the watermarked images as well as high robustness on extracted multiple watermarks.

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APA

Ananth, C., Karthikeyan, M., Mohananthini, N., Saravanan, S., & Swathisriranjani, M. (2019). Multiple watermarking for images using back-propagation neural network and DWT. International Journal of Engineering and Advanced Technology, 9(1), 4088–4093. https://doi.org/10.35940/ijeat.A1327.109119

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