Optimizing the Effect of Cropping and Rotation Attacks on Watermarked Images using Back Propagation Neural Network in DWT Domain
Dr. N. Ramamurthy1, Dr. K. C. T. Swamy2, Gude Ramarao3, H. Shravan Kumar4
1Dr. N. Ramamurthy, Professor, Department of Electronics and Communication Engineering, G. Pullaiah College of Engineering and Technology, Kurnool (A.P) India.
2Dr. K. C. T. Swamy, Associate Professor, Department of Electronics and Communication Engineering, GPCET, Kurnool, (A.P) India.
3Gude Ramarao, Associate Professor, Department of Electronics and Communication Engineering, GPCET, Kurnool, (A.P) India.
4H. Shravan Kumar, Associate Professor, Department of Electronics and Communication Engineering, GPCET, Kurnool, (A.P) India.
Manuscript received on November 25, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 1863-1866 | Volume-9 Issue-2, December, 2019. | Retrieval Number: F9176088619/2019©BEIESP | DOI: 10.35940/ijeat.F9176.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Hiding an image in another image is the technique used for copy write protection. In this proposed work, the watermark is inserted into blue plane of the cover image, In this watermark extraction and embedding process, the back propagation neural network in conjunction with biorthogonal wavelets is utilized to improve the efficiency. The performance is tested by normalized correlation coefficient. The imperceptibility of the watermark is tested by cropping and rotation attacks effectively.
Keywords: Watermark, Wavelets, neural network, rotation, compression.