ISBN: 378-26-138420-01
INTERNATIONAL CONFERENCE ON CURRENT TRENDS IN ENGINEERING RESEARCH, ICCTER - 2014
LITERATURE REVIEW ON GENERIC LOSSLESS VISIBLE WATERMARKING & LOSSLESS IMAGE RECOVERY 1
2
D. Phaneendra,
I.Suneetha,
3
A. Rajani,
M.Tech(DECS) Student,
Associate professor & Head, Assistant professor Department of ECE, AITS Annamacharya Institute of Technology and Sciences,Tirupati,India-517520 1
dorasalaphanendrakumarreddy@gmail.com 2 iralasuneetha.aits@gmail.com 3 rajanirevanth446@gmail.com
retrieved. It is important that the watermarked image must be resistant to common image operations which ensure that the hidden information after alterations is still retrievable without any defect that means the recovered image is same as the original. On the other hand, methods of the visible watermarking yield visible watermarks. These visible watermarks are generally clearly visible after applying common image operations. In addition, ownership information is conveyed directly on the media and copyright violations attempts can be deterred.
Abstract — One way for copyright protection is digital watermarking. Digital watermarking is the process of embedding information regarding the authenticity or the identity of the owners into a image or any piece of data. Digital watermarking has been classified into two types: Visible and Invisible Watermarking. By the use of Reversible watermarking the embedded watermark can be removed and restore the original content. The lossless image recovery is a difficult task but; it is important in most of the applications where the quality of the image is concerned. There are many methods for visible watermarking with lossless image recovery. One to One compound mapping is one of the technique. The compound mapping is reversible and it allows lossless recovery of original images from the watermarked images. Security protection measures can be used to prevent illegal attackers.
In general Embedding of watermarks, degrade the quality of the host media. The legitimate users are allowed to remove the embedded watermark and original content can be restored as needed using a group of techniques, namely reversible watermarking [8-11]. However, lossless image recovery is not guaranteed by all reversible watermarking techniques, which means that the recovered image is same as the original. Lossless recovery is important where there is serious concerns about image quality such as include forensics, military applications, historical art imaging, or medical image analysis.
Key Terms: Reversible visible watermarking, Discrete Cosine Transform (DCT), Discrete Fourier Transform (DFT), Discrete Wavelet Transform (DWT).
I. INTRODUCTION
The
The most common approach is to embed a monochrome watermark using deterministic and reversible mappings of pixel values or DCT coefficients in the watermark region [6,9,11]. Another is to rotate consecutive watermark pixels to embed watermark that is visible [11].the watermarks of arbitrary sizes can be embedded into any host image. Only binary visible watermarks can be embedded using these approaches.
concepts of authenticity and copyright protection are of major importance in the framework of our information society. For example, TV channels usually place a small visible logo on the image corner (or a wider translucent logo) for copyright protection. In this way, unauthorized duplication is discouraged and the recipients can easily identify the video source. Official scripts are stamped or typed on watermarked papers for authenticity proof. Bank notes also use watermarks for the same purpose, which are very difficult to reproduce by conventional photocopying techniques.
The lossless visible watermarking is proposed by using one-to-one compound mappings which allow mapped values to be controllable The approach is generic, leading to the possibility of embedding different types of visible watermarks into cover images. Two applications of the proposed method are demonstrated; where we can embed opaque monochrome watermarks and non-uniformly translucent full-color ones into color images.
Digital Image watermarking methods are usually classified into two types: visible and invisible [1-7]. The invisible watermarking aims to embed copyright information into host media, in case of copyright infringements, to identify the ownership of the protected host the hidden information can be
INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT
180
www.iaetsd.in
ISBN: 378-26-138420-01
INTERNATIONAL CONFERENCE ON CURRENT TRENDS IN ENGINEERING RESEARCH, ICCTER - 2014
• The secret random key. The secret key may be included in the process of watermarking to improve the security during transmission. If a key is also included, only the receiver who knows the key can extract the watermark, and not any intruders.
II. RELATED WORK 2.1 EXISTING WATERMARKING TECHNOLOGIES A. Spatial-Domain technologies
• The masking property of the image. The masking property of the image is also related to the quality and composition of the image which signifies the clarity of the watermark on the original image.
Spatial-domain technologies refer to those embedding watermarks by directly changing pixel values of host images. Some common spatial domain algorithms include Least Significant Bit (LSB). The LSB is the most straight-forward method of watermark embedding. The most serious drawback of spatial-domain technologies is limited robustness.
One form of the data embedding algorithm is given by the equation ,
In the spatial domain, pixels in randomly selected regions of the image are modified according to the signature or logo desired by the author of the product. This method involves modifying the pixel values of the original image where the watermark should be embedded. Fig. 1 shows the block diagram of a spatial-domain data embedding system.
ŷ=y +αI Where y(i,j), is the original image intensity at pixe position (i,j), ŷ is the watermarked image, and αI represents the embedded data in the form of small changes in intensity levels. The author of the watermark holds two keys: • The region of the image where the logo is marked and • The information in the watermark, αI. Given the marked image, the original owner will be able to recover the watermark by comparing the marked image with the original. In the reconstruction of the embedded watermark, the following computation is made, I= (ŷ-y)/α
Fig.1. Spatial domain data embedding system
Randomly selected image data are dithered by a small amount according to a predefined algorithm, whose complexity may vary in practical systems. The algorithm defines the intensity and the position of the watermark on the original image. One of the major disadvantages of the conventional watermarking is that it can be easily extracted from the original image which makes this technique unsuitable for copyright authentication. There are three factors that determine the parameters of the algorithm applied in the spatial domain watermarking. The three factors are: •
Fig. 2. Watermarking result of a color host image. (a) Host image. (b) Logo image. (c) Resulting watermarked Image. (d) Watermark extracted image.
The information associated with the signature. Basically, the signature is the watermark embedded on the original image. The information of the signature is closely related to the size and quality of the signature.
Fig.2. shows the output results of spatial domain technique with host image, logo image, watermarked image and watermark extracted image respectively.
INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT
181
www.iaetsd.in
ISBN: 378-26-138420-01
INTERNATIONAL CONFERENCE ON CURRENT TRENDS IN ENGINEERING RESEARCH, ICCTER - 2014
selected based on a Gaussian network classifier decision. The middle range frequency DCT coefficients are then modified, using either a linear DCT constraint or a circular DCT detection region. A DCT domain watermarking technique based on the frequency masking of DCT blocks was introduced by Swanson. Cox developed the first frequency-domain watermarking scheme. After that a lot of watermarking algorithms in frequency domain have been proposed.
It is difficult for spatial-domain watermarks to survive under attacks such as lossy compression and low-pass filtering. Also the information can be embedded in spatial domain is very limited
B. Frequency-Domain Technologies Compared to spatial-domain watermark, watermark in frequency domain is more robust and compatible to popular image compression standards. Thus frequency-domain watermarking obtains much more attention. To embed a watermark, a frequency transformation is applied to the host data. Then, modifications are made to the transform coefficients. Possible frequency image transformations include the Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT) and others
Figure 3 and Figure 4 illustrate the watermark embedding and detection/extraction in frequency domain, respectively. Most frequency-domain algorithms make use of the spread spectrum communication technique. By using a bandwidth larger than required to transmit the signal, we can keep the SNR at each frequency band small enough, even the total power transmitted is very large. When information on several bands is lost, the transmitted signal can still being recovered by the rest ones. The spread spectrum watermarking schemes are the use of spread spectrum communication in digital watermarking. Similar to that in communication, spread spectrum watermarking schemes embed watermarks in the whole host image. The watermark is distributed among the whole frequency band. To destroy the watermark, one has to add noise with
The first efficient watermarking scheme was introduced by Koch et al. In their method, the image is first divided into square blocks of size 8x8 for DCT computation. A pair of mid-frequency coefficients is chosen for modification from 12 predetermined pairs. Bors and Pitas developed a method that modifies DCT coefficients satisfying a block site selection constraint. After dividing the image into blocks of size 8x8, certain blocks are
INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT
182
www.iaetsd.in
ISBN: 378-26-138420-01
INTERNATIONAL CONFERENCE ON CURRENT TRENDS IN ENGINEERING RESEARCH, ICCTER - 2014
sufficiently large amplitude, which will heavily degrade the quality of watermarked image and be considered as an unsuccessful attack. One major reason why frequency domain watermarking schemes are attractive is their compatibility with existing image compression standards, in particular, the JPEG standard. The compatibility ensures those schemes a good performance when the watermarked image is subject to lossy compression, which is one of the most common image processing methods today.
Fig.6. (a) Three-level Decomposition. (b) Coefficient Distribution.
Besides its own advantages it has a disadvantage that it is not suitable for visible watermarking. And only invisible watermarking is mostly performed in frequency domain.
Furthermore, from these DWT coefficients, the original image can be reconstructed. For reconstruction process same filter must be used. This reconstruction process is called the inverse DWT (IDWT). If I (m, n) represent an image, the DWT and IDWT for I (m, n) can be similarly defined by implementing the DWT and IDWT on each dimension m and n separately.
C. Wavelet-domain Technologies The wavelet transform is identical to a hierarchical sub-band system, where the sub-bands are logarithmically spaced in frequency. The basic idea of the DWT for a two dimensional image is described as follows. An image is first decomposed into four parts of high, middle and low frequencies (i.e. LL1, HL1, LH1, HH1 sub bands) by critically subsampling horizontal and vertical channels using Daubechies filters. The sub-band HL1, LH1 and HH1 represent the finest scale of wavelet coefficients as shown in figure 5. To obtain the next coarser scaled wavelet coefficient, the sub-band LL1 is further decomposed and critically sub-sampled. This process is repeated several times, which is determined by the application in hand. An example of an image decomposed into ten sub-bands for three levels is shown in Figure 6. Each level has various bands information such as low-low, low-high, high-low and high-high frequency bands.
III. CONCLUSION In this paper we have briefly discussed regarding the methods (Spatial domain, Frequency domain and Wavelet domain) which are formerly used in visible watermarking. The former methods used DCT, DFT, DWT and LSB (Least Significant Bit) for desired visible watermarking. A novel method for generic visible watermarking with a capability of lossless image recovery is proposed. The method is based on the use of deterministic one-to-one compound mappings of image pixel values for overlaying a variety of visible watermarks of arbitrary sizes on cover images. The compound map-pings are proved to be reversible, which allows for lossless recovery of original images from watermarked images. The mappings may be adjusted to yield pixel values close to those of desired visible watermarks. Different types of visible watermarks, including opaque monochrome and translucent full color ones, are embedded as applications of the proposed generic approach. A two-fold monotonically increasing compound mapping is created and proved to yield more distinctive visible watermarks in the watermarked image. Security protection measures by parameter and mapping randomizations have also been proposed to deter attackers from illicit image recoveries. Experimental results demonstrating the effectiveness of the proposed approach are also included.
Fig.5. Three level wavelet decomposition
INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT
183
www.iaetsd.in
ISBN: 378-26-138420-01
INTERNATIONAL CONFERENCE ON CURRENT TRENDS IN ENGINEERING RESEARCH, ICCTER - 2014
Trends in Engineering, Vol. 1, No. 1, pp. 430433, May 2009. [13] Mohammad Reza Soheili “A Robust Digital image Watermarking Scheme Based on DWT” Journal of Advances in Computer Research, m2(2010) 75-82.1. [14] R.AARTHI, V. JAGANYA, & S. POONKUNTRAN “Modified Lsb Watermarking For Image Authentication” International Journal of Computer & Communication Technology (IJCCT) ISSN (ONLINE): 2231 - 0371 ISSN (PRINT): 0975 – 7449 Vol-3, Iss-3, 2012. [15] Vaishali S. Jabade and Dr. Sachin R. Gengaje, “Literature Review of Wavelet Based Digital Image Watermarking Techniques”, International Journal of Computer Applications, Vol 31, No.1, pp. 28-35, October 2011.
REFERENCES [1] G. Braudaway, K. A. Magerlein, and F. Mintzer, “Protecting publicly available images with a visible image watermark,” in Proc. SPIE Int. Conf. Electronic Imaging, Feb. 1996, vol. 2659, pp. 126–133. [2] I. J. Cox, J. Kilian, F. T. Leighton, and T. Shamoon, “Secure spread spectrum watermarking for multimedia,” IEEE Trans. Image Process., vol. 6, no. 12, pp. 1673– 1687, Jun. 1997. [3] F.A.P Patitcolas, R.J.Anderson, and M.G.Kun“Information hiding- A survey”Proc.IEEE, vol:87, no.7, jul. 1999. [4] M. S. Kankanhalli, Rajmohan, and K. R. Ramakrishnan, “Adaptive visible watermarking of images,” in Proc. IEEE Int. Conf. Multimedia Computing and Systems, 1999, vol. 1, pp. [5] S. P. Mohanty, K. R. Ramakrishnan, and M. S Kankanhalli, “A DCT domain visible watermarking technique for images,” in Proc. IEEE Int. Conf. Multimedia and Expo, Jul. 2000, vol. 2, pp. 1029– 1032. [6] N. F. Johnson, Z. Duric, and S. Jajodia, Information Hiding. Steganography and Watermarking Attacks and Countermeasures. Boston, MA: Kluwer, 2001. [7] Y. Hu and S.Kwong,“Wavelet domain adaptive visiblewatermarking,” Electron. Lett., vol. 37, no. 20, pp. 1219–1220, Sep. 2001. [8] Y. J. Cheng and W. H. Tsai, “A new method for copyright and integrity protection for bitmap images by removable visible watermarks and irremovable invisible watermarks,” presented at the Int. Computer Symp. Workshop on Cryptology and Information Security, Hualien,Taiwan, R.O.C., Dec. 2002. [9] P. M. Huang and W. H. Tsai, “Copyright protection and authentication of grayscale images by removable visible watermarking and invisible signal embedding techniques: A new approach,” presented at the Conf. Computer Vision, Graphics and Image Processing, Kinmen, Taiwan, R.O.C., Aug. 2003. [10] Y. Hu, S. Kwong, and J. Huang, “An algorithm for removable visible watermarking,” IEEE Trans. Circuits Syst. Video Technol., vol. 16, no. 1, pp. 129– 133, Jan.2006. [11] S. K. Yip, O. C. Au, C. W. Ho, and H. M. Wong, “Lossless visible watermarking,” in Proc. IEEE Int. Conf. Multimedia and Expo, Jul. 2006, pp. 853–856.” [12] Neminath Hubballi and Kanyakumari D P, “Novel DCT based watermarking scheme for digital images”, International Journal of Recent
INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT
184
www.iaetsd.in