1. Robust Digital Image Watermarking using DCT based Pyramid Transform via image compression
Authors: Jagdish Prasad Maheshwari, Mahendra Kumar, Garima Mathur, R P Yadav, Rajesh Kumar Kakerda
Presented By:
Mahendra Kumar
Faculty at UCE, RTU, Kota (Raj.) India
Director, MI Tech Society, Kota (Raj.) India

2. CONTENTS Introduction Classification of watermark Algorithms
Basic Requirement for a Digital Watermark Algorithm
Distortions and Attacks
Laplacian Pyramid
DCT based Laplacian Pyramid transform
Image Watermarking Process
Fusion Performance Evaluation
Experimental results
Conclusion
References

3. Motivation Copying images is easy Distributing images is easy
But what if we want to protect our rights to an image?

4. Watermarking Embedding data into an image Format may change
Data must be stored in the actual pixels

5. Applications Copyright identification Fingerprinting
Authenticity determination
Monitoring
Data hiding

6. Introduction
This paper presents a DCT based pyramid transform watermarking scheme for ownership verification of digital images.
In digital watermarking, a watermark is embedded into a cover image in such a way that the resulting watermarked signal is robust to certain distortions caused by either standard data processing in a friendly environment or malicious attacks in an unfriendly environment.
This paper provides Digital Image Watermarking based on DCT based pyramid transform with malicious JPEG compression attack.
Signal to Noise Ratio (SNR) is computed to measure image quality for proposed technique for better results as compared to previous techniques of information hiding.

7. Classification Of Watermark Algorithms
Visible Watermarking (alpha>0.1): Visible watermarking is easily perception by the human eye, means the visible watermark can be seen without the extraction process. For example it can be name or logo of the company.
Invisible Watermarking (alpha<0.1): In this watermarking mark cannot be seen by human eye. It is embedded in the data without affecting the content and can be extracted by the owner only.

8. Basic Requirement for a Digital Watermark Algorithm
Figure 2: Watermark Extraction Process
Figure 1: Watermark Embedding Process

9. Distortions and Attacks
Hostile or malicious attacks, which are an attempt to weaken, remove or alter the watermark, and
Coincidental attacks, which can occur during common image processing and are not aimed at tampering with the watermark.
Removal attacks attempt to separate and remove the watermark.
Compression: Practically all images currently being distributed via Internet have been compressed.

10. Laplacian pyramid
The Laplacian pyramid was first introduced as a model for binocular fusion in human stereo vision [3], where the implementation used a Laplacian pyramid and a maximum selection rule at each point of the pyramid transform.
Essentially, the procedure involves a set of band-pass copies of an image is referred to as the Laplacian pyramid due to its similarity to a Laplacian operator.
Each level of the Laplacian pyramid is recursively constructed from its lower level by applying the following four basic steps: blurring (low-pass filtering);sub-sampling (reduce size); interpolation (expand); and differencing (to subtract two images pixel by pixel).
In the Laplacian pyramid, the lowest level of the pyramid is constructed from the original image [5].

11. Information flow diagram of pyramid a). Construction & b)
Information flow diagram of pyramid a). Construction & b). Reconstruction[5].

12. DCT based Laplacian Pyramid Transform
The procedure for Laplacian pyramid construction and reconstruction is illustrated in Fig-1.
Reduced Function: The image at the 0th level g0 of size MxN is reduced to obtain next level g1 of size 0.5Mx0.5N where both spatial density and resolution are reduced. Similarly, g2 is the reduced version of g1 and so on. Image reduction is done by taking the DCT and applying the IDCT on first half of coefficients in both directions. The level to level image reduction is performed using the function reduce R.
Expand Function: The reverse of function reduces is expanded function E. Its effect is to expand the image of size MxN to image of size 2Mx2N by taking IDCT after padding the M zeros in horizontal and N zeros in vertical directions.

13. Digital Image Watermarking Process
Let, there are two images (I1 & I2) to be fused. Pyramid construction is done for each image and keeping the error records. Denote the constructed k levels of Laplacian image pyramid for 1st image (Host Image) is [5]
and similarly for of 2nd image (Watermark Image) is
Then the image 2 is watermarked into image 1 as follows
Watermarked_image= DCTPT(image1) + alpha*DCTPT(image2)
Extract Watermark= (Watermarked_image - DCTPT (image1))/alpha

14. For k-1 to 0 levels
and the magnitude comparison is done on corresponding pixels. The pyramid If = g0f the fused image.

15. Fusion Performance Evaluation
Peak Signal to Noise Ratio:
This value will be high when the fused and reference images are alike and higher value implies better fusion.
where, L in the number of gray levels in the image.

16. Experimental Results Of Proposed Technique
Original image
Embedding watermark image

17. vary alpha and constant q
Table 1
vary alpha and constant q
Alpha
q(quality factor)
DCTPT
(PSNR)
FRFT
FFT
0.2 80
0.1
0.05
0.03
0.01

18. Fig. : chart for PSNR v alpha and constant q

19. Table 2: constant alpha and vary q
q(quality factor)
DCTPT
(PSNR)
FRFT
PSNR
FFT
0.05 30 50 70 80 90
100

20. Fig. : chart for PSNR v q and constant alpha

21. Conclusion
In this paper, different watermarking scheme such as FFT, FRFT and DCT based Pyramid Transform technique apply, the process is the same.
We can note that DCT based Pyramid transform scheme more robust than FRFT & FFT scheme due to PSNR of DCT based Pyramid transform based watermarking technique is better comparatively Previous exiting techniques based watermarking scheme as shown in table 1 and chart shown in fig 5& 6.

22. REFERENCES
[1] Edin Muharemagic and Borko Furht, “Survey Of Watermarking Techniques And Applications”, Department of Computer Science and Engineering, Florida Atlantic University.
[2] Andreja Samˇcovi´c, J´an Tur´an, “Attacks on Digital Wavelet Image watermarks”, Journal of Electrical Engineering.
[3] Peining Taoa and Ahmet M. Eskicioglub, “A robust multiple watermarking scheme in the Discrete Wavelet Transform domain”, The Graduate Center, The City University of New York.
[4] Baisa L. Gunjal, “An Overview Of Transform Domain Robust Digital Image Watermarking Algorithms”, Department of Computer Engineering, Amrutvahini College of Engineering.
[5] Igor Djurovic, Srdjan Stankovic, and Ioannis Pitas,” Digital watermarking in the fractional Fourier transformation domain”, Journal of Network and Computer Applications (2001), page 167 – 173.
[6] Vaishali.S.Jabade, Dr.Sachin R.Gengaje “Literature Review of Wavelet based Digital Image Watermarking Techniques”, International Journal of Computer Applications, Vol.31, No.1, October2011.
[7] P. Meerwald, A. Uhl, “A Survey of Wavelet-DomainWatermarking Algorithms”, EI San Jose, CA, USA, 2001.
[8] Mohamed A. Suhail and Mohammad S. Obaidat, "Digital Watermarking-Based DCT and JPEG Model", IEEE Transactions On Instrumentation and Measurement, Vol. 52, NO. 5, p , October 2003.
[9] Mahendra Kumar et. al., “Implementation of Different Non-Recursive FIR Band-pass filters using Fractional Fourier Transform” in proceedings of 4th IEEE International Conference on Computational Intelligence and Communication Networks (CICN-2012), Mathura, 3-5 Nov
[10] Mahendra Kumar et. al., “Digital image watermarking: A survey”, International Journal of Engineering and research applications (IJERA), Jul-Aug, 2013.
[11] Mahendra Kumar et.al., “Digital Image Watermarking using Fractional Fourier transform via image compression”, In IEEE International Conference on Computational Intelligence and Computing Research 2013 (IEEE ICCIC-2013), Dec., 2013.
[12] VPS Naidu, “A Novel Image Fusion Technique using DCT based Laplacian Pyramid”, International Journal of Inventive Engineering and Sciences (IJIES) ISSN: 2319–9598, Volume-1, Issue-2, January, 2013.
[13] Mahendra Kumar et. al., “Digital Image Watermarking using Fractional Fourier Transform with Different Attacks” International Journal of Scientific Engineering and Technology, Volume No. 3 Issue No. 8, Aug. 2014, pp: , (ISSN : ).