Abstract: This paper presents a new robust digital image watermarking technique based on relation between wavelet coefficients transform and neural network. The neural network is Full Counter propagation Neural Network (FCNN). FCNN has been used to simulate the perceptual and visual characteristics of the original image. The perceptual features of the original image have been used to determine the highest changeable threshold values of DWT coefficients. The highest changeable threshold values have been used to embed the watermark in DWT coefficients of the original image. The watermark is a binary image. The pixel values of this image are inserted as zero and one values in the DWT coefficients of the image. The implementation results have shown that this watermarking algorithm has excellent robustness versus different kinds of watermarking attacks.
Keywords: Digital Image Watermarking, Discrete Wavelet Transform, Neural Network, Human Visual System.
Title: A New Robust Digital Image Watermarking Technique Using Relations between Wavelet Coefficients Transform and Full Counter Propagation Neural Network
Author: Ayoub Taheri
ISSN 2349-7815
International Journal of Recent Research in Electrical and Electronics Engineering (IJRREEE)
Paper Publications
