Research Article Open Access

Blind Digital Image Watermarking Robust Against Histogram Equalization

G. S. Kalra1, R. Talwar2 and H. Sadawarti2
  • 1 Lovely Professional University Punjab, India
  • 2 Punjab Technical University, India
Journal of Computer Science
Volume 8 No. 8, 2012, 1272-1280

DOI: https://doi.org/10.3844/jcssp.2012.1272.1280

Submitted On: 15 December 2011 Published On: 14 July 2012

How to Cite: Kalra, G. S., Talwar, R. & Sadawarti, H. (2012). Blind Digital Image Watermarking Robust Against Histogram Equalization. Journal of Computer Science, 8(8), 1272-1280. https://doi.org/10.3844/jcssp.2012.1272.1280

Abstract

Problem statement: Piracy in the presence of internet and computers proves to be a biggest damage to the industry. Easy editing and copying of images yields a great damage to the owner as original images can be distributed through internet very easily. To reduce the piracy and duplicity of the digital multimedia files, digital watermarking technique is dominating over the other available techniques. There are certain methods or attacks which are used to damage the watermark. One of the major attacks is histogram equalization and reducing the number of histogram equalized levels. Thus, there is a need to develop a method so that the watermark can be protected after histogram equalization. Approach: A blind digital watermarking algorithm is presented which embed the watermark in frequency domain. Firstly, DWT is applied on the original image and then DCT on the 4×4 blocks to target the particular frequencies of the image for embedding the watermark which does not have more effect after histogram equalization. Also, to enhance the security of the watermark dual encryption technique is deployed. Results: Algorithm applied to four images which are Lena, Cameraman, Baboon and Peppers. The evaluation of the algorithm is calculated in terms of peak signal to noise ratio and non correlation. The results prove that the algorithm is robust to histogram equalization attack up to 2 grey levels. Conclusion/Recommendations: The developed algorithm proved its performance against histogram equalization but the algorithm can also be checked for the other attacks which can be addition of white noise, Gaussian noise, filtering.

  • 1,428 Views
  • 2,222 Downloads
  • 1 Citations

Download

Keywords

  • Watermarking
  • image
  • dwt
  • frequency domain robust
  • blind
  • histogram equalization