{"id":1204,"date":"2018-12-04T05:34:01","date_gmt":"2018-12-04T05:34:01","guid":{"rendered":"http:\/\/www.gyanvihar.org\/journals\/?p=1204"},"modified":"2019-05-22T10:44:43","modified_gmt":"2019-05-22T10:44:43","slug":"rotation-attack-analysis-of-non-blind-multiplicative-watermarking-using-2d-dwt","status":"publish","type":"post","link":"https:\/\/www.gyanvihar.org\/journals\/rotation-attack-analysis-of-non-blind-multiplicative-watermarking-using-2d-dwt\/","title":{"rendered":"Rotation attack analysis of Non Blind Multiplicative Watermarking using 2D-DWT"},"content":{"rendered":"

1<\/sup>Rohit Chhabra, 2<\/sup>R R Sinha<\/strong><\/p>\n

1<\/sup><\/em>Rohitengineer14@gmail.com<\/em>, 2<\/sup><\/em>drsinhacs@gmail.com,<\/em><\/p>\n

Associate Professor, Department of Computer Engineering, Suresh Gyan vihar university, Jaipur,Rajasthan India<\/em><\/p>\n

Abstract: This paper deals with the digital ownership management with the help of Digital watermarking. For inserting any ownership information in any form inside the image or any media like audio video etc, we need a digital watermarking embedding and extraction algorithm, so that owner of the digital object will be able to identify and claim his\/her ownership when any illegal person claim his\/her false ownership on that object by extracting the watermark. In this research paper, we give a comparison between two watermarking algorithm based on DWT one on additive\u00a0embedding strategy i.e. ASG algorithm and second one on multiplicative embedding strategy is kedia algorithm. Robustness in term of rotation attack of both the algorithm & tested in terms of PSNR and SNR and compared.<\/strong><\/p>\n

 <\/p>\n

Keywords: <\/em><\/strong>DWT, PSNR, SNR, Watermarking, Robustness, Additive embedding, Multiplicative embedding.<\/p>\n

 <\/p>\n

I. INTRODUCTION<\/p>\n

There is a strong need for security services in order to keep the distribution of digital multimedia work both profitable for the document owner and reliable for the customer. Watermarking technology plays an important role in securing the business as it allows placing an imperceptible mark in the multimedia data to identify the legitimate owner, to track authorized user. Digital watermarking is one of the method to maintain the digital ownership management. There are various ways to embed the watermark by various algorithm here we have taken ASG algorithm as base algorithm and compared this algorithm with the Kedia algorithm. After that we analysis the robustness of kedia algorithm by using rotation attack.<\/p>\n

II. PREVIOUS WORK
\nSreenivasan [1] had Implemented Digital Watermarking using\u00a0discrete 2-D wavelet transform and Input image is termarked with a key having Mean = 0 & Variance = 1.\u00a0This key was generated by utilizing the abstract white\u00a0Gaussian noise (awgn). Up to my best knowledge this\u00a0algorithm is available only for embedding the watermark and\u00a0can be improved for extraction<\/p>\n

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ASG algorithm [2], also uses Discrete Wavelet Transform\u00a0(DWT) and additive embedding strategy for embedding and\u00a0extracting watermark image from the host image. Kedia[11]\u00a0Algorithm has attempted to bring out the algorithm of ASG\u00a0[2] in a better way by using multiplicative embedding strategy\u00a0for watermark embedding and extraction and then analyzing\u00a0the PSNR and SNR of the extracted watermark with original\u00a0watermark and between original image and watermarked\u00a0image without attack.In Proposed algorithm Kedia Algorithm\u00a0is analysis & comparisons of ASG & Kedia algorithm by\u00a0rotation attack with SNR & PSNR Values for test the\u00a0robustness of the algorithm.<\/p>\n

 <\/p>\n

III. RESULT OBTAINED BY KEDIA ALGORITHM<\/p>\n

Kedia algorithm imperceptibility evaluated by calculating\u00a0SNR between original image and watermarked image in\u00a0Decibels (db), PSNR between original image and\u00a0watermarked image in Decibels (db), SNR between original\u00a0watermark and extracted watermark in Decibels(db), PSNR\u00a0between original watermark and extracted watermark in\u00a0Decibels(db).\u00a0Signal-to-noise ratio (often abbreviated SNR or S\/N): It is\u00a0defined as the ratio of signal power to the noise power. A\u00a0ratio higher than 1:1 indicates more signal than noise.<\/p>\n

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Figure 1. Upper graph shows SNR values between original image and watermarked image for ASG Algorithm and lower graph SNR values between original image and watermarked image for Kedia Algorithm.<\/p>\n

Figure 1 shows SNR for various test images show that ratio of SNR is greater than 1:1 ratio for all test images; it means that the value of the signal is greater than the noise.<\/p>\n

Noise is the difference between the original image and watermarked image, this difference will show the strength of watermark signal that obscure the original image, least the value of this watermark signal lessen the amount of obscuring the original image i.e. more value of SNR will shows that there is less amount damage in original image. For both the Kedia algorithm and ASG algorithm simulation result shows that the value of SNR is between 39 to 45 that shows degradation in original test image by the watermark signal is very less.<\/p>\n

More value of SNR will show less amount of damage in extracted watermark. For both the Kedia algorithm and ASG algorithm simulation result shows that the value of SNR is between 37 to 60 that shows extracted watermark image degradation is very less after extraction process.<\/p>\n

\"\"<\/p>\n

Figure 2 Upper Graph showing SNR values between original and extracted watermark by ASG algorithm and Lower graph by Kedia algorithm.<\/p>\n

A. SNR Result Conclusion<\/p>\n

(i)The amount of original data presence in watermarked image is more than the background noise. i.e. extracted watermark is recognizable for identity proof.<\/p>\n

(ii)Kedia algorithm has higher values of SNR so that we can say that Kedia algorithm has more value of original signal i.e. more matching of the extracted watermark with original watermark so it is better than ASG algorithm.<\/p>\n

(iii)Peak signal-to-noise ratio, often abbreviated PSNR, is an engineering term for the ratio between the maximum possible power of a signal and the power of corrupting noise that affects the fidelity of its representation. Because many signals have a very wide dynamic, PSNR is usually expressed in terms of the logarithmic decibel scale [3].<\/p>\n

As a measure of quality of reconstruction of lossy\u00a0compression codecs (e.g., for image compression) PSNR is\u00a0used. The signal in this case is the original data, and the noise\u00a0is the error introduced by compression. When comparing\u00a0compression codecs it is used as an approximation to human\u00a0perception of reconstruction quality, therefore in some cases\u00a0one reconstruction may appear to be closer to the original\u00a0than another, even though it has a lower PSNR (a higher\u00a0PSNR would normally indicate that the reconstruction is of\u00a0higher quality). One has to be extremely careful with the\u00a0range of validity of this metric; it is only conclusively valid\u00a0when it is used to compare results from the same codec (or\u00a0codec type) and same content [3].\u00a0Typical values for the PSNR in lossy image and video\u00a0compression are between 20 and 50 dB [3]<\/p>\n

IV. RESULT OBTAINED BY PROPOSED ALGORITHM
\nDuring transmission and even after reception of watermarked\u00a0image due to some impairments like introduction of Noise,\u00a0Image Cropping, Resizing, image get blur and dither, diluted\u00a0as well as erode which change the position of watermark ,\u00a0sometimes destroy watermark .which is undesirable for\u00a0owners of image so it become necessary to analyze robustness\u00a0of watermarking algorithm [4].<\/p>\n

\"\"<\/p>\n

\"\"<\/p>\n

\"\"<\/p>\n

value of SNR for various test images between watermarked\u00a0image and watermarked image after attack is 18.90 which\u00a0mean that the quality of the watermarked image is degraded\u00a0by the attack to a very little extent as the average value of\u00a0SNR is 42.19 without attack.<\/p>\n

\"\"<\/p>\n

\"\"<\/sup><\/em><\/p>\n

Figure 3 upper Graph showing SNR values between original image and watermarked image after Rotation Attack by ASG algorithm and under graph by Kedia algorithm.<\/p>\n

B. SNR Result Conclusion with rotation attack<\/p>\n

(i)Watermarked image withstand the rotation attack by\u00a0both the algorithm.\u00a0(ii)Kedia algorithm SNR values is far better than the ASG\u00a0algorithm so watermarked image withstand strongly rotation\u00a0attack when it is watermarked by Kedia algorithm.\u00a0SNR values between original watermark image and\u00a0extracted watermark image after rotation attack are plotted in\u00a0Figure 4.for various test images.<\/p>\n

\"\"<\/p>\n

\"\"<\/p>\n

Figure 4 LUpper Graph showing SNR values between original watermark and extracted watermark after Rotation Attack by ASG algorithm and under graph by Kedia algorithm for various test images<\/p>\n

C. SNR Result Conclusion of Extracted Watermark with\u00a0rotation attack
\n(i)Extracted watermark withstand the rotation attack when\u00a0watermarked by both the algorithm.
\n(iii)Value of SNR by Kedia algorithm is far better than\u00a0ASG algorithm so Kedia algorithm is better withstand the\u00a0rotation attack.<\/p>\n

PSNR values between watermarked image and rotated\u00a0watermarked image after rotation attack are plotted in Figure\u00a07 Left Graph showing PSNR values between Original\u00a0Watermark and Extracted watermark image after Rotation\u00a0Attack by ASG algorithm and right graph by Kedia algorithm.<\/p>\n

\"\"<\/p>\n

\"\"<\/p>\n

D. PSNR Result Conclusion of with rotation attack
\n(i)Watermarked image withstand the rotation attack when\u00a0embedded by both image.
\n(ii)Value of PSNR by Kedia algorithm is far better than\u00a0ASG algorithm so Kedia algorithm is better withstand the\u00a0rotation attack.\u00a0PSNR values between original watermark image and\u00a0extracted watermark image after rotation attack are plotted in\u00a0Figure 8 for various test images.<\/p>\n

\"\"<\/p>\n

\u00a0<\/sup><\/em><\/p>\n

Figure 6. Left Graph showing PSNR values between original watermark image and Extracted watermark image after Rotation Attack by ASG algorithm and right graph by Kedia algorithm.<\/p>\n

E. PSNR Result Conclusion of Extracted Watermark with\u00a0rotation attack
\n(i)Extracted Watermarked image withstand the rotation\u00a0attack when embedded by both image.
\n(ii)Value of PSNR by Kedia algorithm is far better than\u00a0ASG algorithm so Kedia algorithm is better to withstand the
\nrotation attack.<\/p>\n

V. CONCLUSION
\nAfter attacking the Kedia algorithm with Rotational attack\u00a0and then comparing the PSNR and SNR values with ASG
\nalgorithm we found that the Kedia algorithm is far better than\u00a0the ASG algorithm as we get more values of PSNR and SNR\u00a0between original watermark and extracted watermark after\u00a0attack than the ASG algorithm. Similarly we get more values\u00a0of the PSNR and SNR between original image and\u00a0watermarked image after attack than ASG algorithm. Also we\u00a0can say that Kedia algorithm is robust for the rotational attack\u00a0and imperceptible<\/p>\n

VI. REFERENCES
\nThe heading of the References section must not be numbered.\u00a0All reference items must be in 8 pt font. Please use Regular\u00a0and Italic styles to distinguish different fields as shown in the\u00a0References section. Number the reference items\u00a0consecutively in square brackets (e.g. [1]).<\/p>\n

    \n
  1. Abhijith Sreenivasan (2007 1 Feb), Simple Watermarking using\u00a0Wavelet transform, (1st ed),\u00a0[Online]Availiable:http:\/\/www.mathworks.com\/matlabcentral\/fileexcha\u00a0nge\/13834-simple-water-marking-using-wavelet-transform.<\/li>\n
  2. ASG, \u201cNon blind Discreet Wavelet Transformation based Digital\u00a0Watermark Embedding and Extraction Algorithm\u201d, Master Thesis,\u00a0Dept. of Comp. Science and Information Technology, Rajasthan\u00a0Technical University, Kota, Rajasthan, India, 2012.<\/li>\n
  3. Wikipedia, Peak Signal to Noise Ratio (44 ed.) [Online] Available:\u00a0http: \/\/ en. wikipedia. org \/wiki\/Peak_signal-to-noise_ratio.<\/li>\n
  4. Navnidhi Chaturvedi, Dr.S.J.Basha ,\u201c Analysis of Image Water marking\u00a0by DWT and Performance Under Attacks\u201d International Journal of\u00a0Computer Technology and Electronics Engineering (IJCTEE) Volume\u00a02, Issue 3, June 2012<\/li>\n
  5. \u201cDigital watermarking a technology overview\u201d Hebah H.O.\u00a0Nasereddin,IJRRAS 6 (1) , January 2011<\/li>\n
  6. Digital Watermarking Techniques: Literature Review<\/li>\n
  7. http:\/\/www.digitavid.net\/VirtualUniversity\/Presentations\/ImagingWatermarking.pdf<\/li>\n
  8. Ingemer J.Cox, Joe Killan, Tom Leighton and Talal G. Shamoon,\u00a0\u201cSecure spread spectrum watermarking for multimedia\u201d, IEEE proceeding International Conference on\u00a0 Image Processing, vol.6, pp\u00a01673-1687 Santa Barbara, California, USA, October 1997.<\/li>\n
  9. George Voyatzis and loannis Pitas, \u201cApplication of toral\u00a0automorphisms in image watermarking\u201d, IEEE proceeding of\u00a0International Conference on Image processing, vol. 2, pp 237-240,\u00a0Lausanne, Switzerland, September 1996. IEEE press.<\/li>\n
  10. Thesis on Digital Watermarking in the Wavelet Transform Domain by\u00a0Peter Meerwald 11, January 2001.<\/li>\n
  11. Naveen Kumar Kedia,Saroj Hirenwal,\u201d Non Blind Digital\u00a0Watermarking using 2D- DWT,June 2013\u201d, International Journal of\u00a0Emerging Technology and Advanced Engineering, Volume 3, Issue 6.<\/li>\n<\/ol>\n

    \n","protected":false},"excerpt":{"rendered":"

    1Rohit Chhabra, 2R R Sinha 1Rohitengineer14@gmail.com, 2drsinhacs@gmail.com, Associate Professor, Department of Computer Engineering, Suresh Gyan vihar university, Jaipur,Rajasthan India Abstract: This paper deals with the digital ownership management with the help of Digital watermarking. For inserting any ownership information in any form inside the image or any media like audio video etc, we need a […]<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[26,31],"tags":[],"class_list":["post-1204","post","type-post","status-publish","format-standard","hentry","category-international-journal-of-converging-technologies-management","category-volume-3-issue-1-2017"],"yoast_head":"\nresearch journal - Research Journal<\/title>\n<meta name=\"description\" content=\"Rotation Attack Analysis Of Non Blind Multiplicative Watermarking Using 2d-dwt Journal Written By Rohit Chabbra. 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