
	Journal of Applied Sciences
	Year: 2011 \| Volume: 11 \| Issue: 16 \| Page No.: 2907-2915 DOI: 10.3923/jas.2011.2907.2915

Determining Watermark Embedding Strength using Complex Valued Neural Network

R.F. Olanrewaju, O.O. Khalifa, Aisha- Abdulla, A.A. Aburas and A.M. Zeki

Abstract: The requirements needed for an effective and proficient watermarking system is application dependent. However, robustness and image quality (imperceptibility) are fundamental requirements for applications that deal with image watermarking. The major factor that affects the robustness and imperceptibility is the watermark embedding strength. In this study, a CVNN based adaptive technique of estimating watermark embedding strength for a digital image is presented. Experimental results indicated that CVNN based method can estimate the watermarking strength, gives a better correlation and an improved imperceptibility of the watermarked image. It also demonstrates that the detection is enhanced. The use of this new method in watermarking achieved content authentication and helps overcome the problem of visual artifacts and distortions created during watermark embedding.

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How to cite this article:

R.F. Olanrewaju, O.O. Khalifa, Aisha- Abdulla, A.A. Aburas and A.M. Zeki, 2011. Determining Watermark Embedding Strength using Complex Valued Neural Network. Journal of Applied Sciences, 11: 2907-2915.

DOI: 10.3923/jas.2011.2907.2915

URL: https://scialert.net/abstract/?doi=jas.2011.2907.2915

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