Robust Adaptive Watermarking Using Local Complexity Variation

Due to increasing use of computer networks and Internet, digital contents can nowadays be easily exchanged. As a result many copyrighted contents may be shared illegally and this has concerned multimedia owners. In order to overcome this problem, watermarking schemes have been proposed to protect copyright of digital contents such as digital images, in spatial and transform domains.  Transform domain methods have attracted more attention because they are more robust against possible attacks.  Robustness and visual quality are two conflicting features that should be attained at the same time in a proper watermarking scheme.  Obtaining these features require high computational complexity, which makes it inappropriate for use in many real-time watermarking applications.  Therefore, improving the computational complexity of complicated watermarking techniques by decreasing execution time has become a challenge.  In this project a new image-adaptive watermarking framework is introduced and based on this framework three robust watermarking schemes are proposed.  All of the proposed watermarking algorithms are blind methods which embed binary logos as watermark in cover images.  These methods properly adjust the strength factor while maintain visual quality of image.  Experimental results verify this fact and show that proposed schemes have good robustness against usual image processing attacks while preserving fidelity of watermarked images.


Figure. 1.   (a) Original “Lena” image, (b) initial 32×32 binary watermark logo, and (c) watermarked
image with PSNR= 45.72 dB and MSSIM = 0.997.


Extracted Papers:

S. Azizi, S. Samavi, M. Mohrekesh and S. Shirani, "Cascaded transform space watermarking based on analysis of local entropy variation," In proceeding of International Conference on Multimedia and Expo Workshops (ICMEW), pp. 1-6, San Jose, California, July 2013.

S. Azizi, M. Mohrekesh, S. Samavi and S. Shirani, "Hybrid image watermarking using local complexity variations," In proceeding of Iranian conference on Electrical Engineering (ICEE), pp. 1-6, May 2013.


this is  an image.