A. K. Verma

Work place: Department of Electrical and Electronics Engineering, Hindustan Institute of Technology and Management, Agra, UP, India

E-mail: ajaykrverma@yahoo.com

Website: https://www.researchgate.net/profile/A-Verma-4

Research Interests: Signal Processing, Image Processing


Dr. A. K. Verma is working in Hindustan Institute of Technology and Management, Agra, UP, India as Associate Professor in the department of Electrical and Electronics Engineering. He obtained his B.Sc.-Engg. in Electrical Engineering in year 2000 and M.Tech. in Engg. Systems in year 2002 from Dayalbagh Educational Institute (DEI). He was awarded with Gold Medals in both B.Sc.-Engg. and M.Tech. for securing highest marks. He has obtained his Ph.D. in March 2014 from DEI. His areas of research is wavelets and their applications in Signals and Image Processing. He has published more than 25 research papers in various international journals and conferences of repute. He is also reviewer of few international conferences. Dr. Verma is life member of ISTE, India.

Author Articles
Robust Adaptive Watermarking Based on Image Contents Using Wavelet Technique

By A. K. Verma C. Patvardhan C. Vasantha Lakshmi

DOI: https://doi.org/10.5815/ijigsp.2015.02.07, Pub. Date: 8 Jan. 2015

A good watermarking scheme should be able to perform equally well on all types of images irrespective of image contents because practically watermarking has to be applied to images of all types. In this paper, it is shown that in wavelet based spread spectrum technique, watermarking at level 1 decomposition is better for textured images while watermarking at level 2 decomposition is better for non-textured images to achieve maximum robustness against various types of attacks. The proposed wavelet decomposition level selection algorithm utilizes the edge histogram to classify the host image as textured or non-textured image and automatically selects the level of decomposition for robust watermarking. The use of Spread Spectrum watermarking technique and Bior6.8 wavelet, results better robustness. Performance of the proposed scheme and its relative effectiveness is demonstrated on both categories of images under different attacks.

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