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  1. 1. Mr. Krunal R patel Mr .Lokesh P. Gagnani / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 1, January -February 2013, pp.840-846 Current classification and introduction of Watermarking Techniques in Digital Images Mr. Krunal R patel Mr .Lokesh P. Gagnani, 1P.G student of KIRC,kalol 2Asst.Prof. KIRC,kalolAbstract — This paper surveys recent advances in than one hundred institutes around the world [1]watermarking techniques in digital images. The whichaim of digital watermarking is to include deal with the issue. The application of watermarkingsubliminal information in multimedia ranges from copyright protection, file tracking andinformation to ensure a security service or simply monitoring. It was proposed in [16] one of a maina labelling application. It would be then possible classification structures of watermarking recover the embedded message at any time, This is shown in Figure 1. From this classification,even if the information was altered by one or there are two types of watermarks, the visible ones,more non-destructive attacks, whether malicious like different logos either on paper or on a TVor not. Its commercial applications range from screen and the most important one, the invisible orcopyright protection to digital right management. transparent watermarks, which cannot be perceivedThis paper then classifies the different by the human sensory system. An invisiblewatermarking techniques into several categories watermark can be either robust or fragile. The use ofdepending upon the domain in which the hidden a fragile watermark is important when one wants todata is inserted; the size of the hidden data and verity if the protected media was tampered with orthe requirement of which the hidden data is to be not. The type of watermark is especially designed toextracted, An experiment is conducted to further be as fragile as possible, so even the slightesttests the robustness of some of these techniques. modification of the marked media will destroy it,At the end, this paper analyses challenges that indicating that someone tampered with the media inhave not been met in current watermarking question. This type of watermark is like a CRCtechniques here . In my major work describes a (cyclic redundancy code). On the other hand, robustwatermark embedding technique for images watermarking is designed to provide proof ofusing discrete fractional Fourier transform. ownership of the media in question. Recently, it is used as one of the means of Digital RightKeywords — Management. This paper concerns with the surveyWatermarking, Advance Techniques, Challenges, of this category of digital image watermarking andDFRFT,proposed work henceforth will be referred to as watermarking only for brevity. A watermarking system conceals information insideI.INTRODUCTION some other data. There are three criteria that can be Digital watermarking technology is now used to measure the performance of a watermarkingdrawing the attention as a new method of protecting system. They are Embedding Effectiveness, Fidelitycopyrights for digital images. It is realized by and Data payload, different application has differentembedding data that is insensible for the human preferences based on its nature and requirements [2]visual system. The embedded information data is We define embedding effectiveness of acalled watermark. So watermarking in digital watermarked work as a work that when input to aimages is the process by which a discrete data detector results in a positive detection. With thisstream is hidden within an image imposing definition of watermarked works, the effectivenessimperceptible changes of the image. The root of of a watermarking system is the probability that thewatermarking as an information hiding technique output of the sender will be watermarked. In othercan be traced in ancient Greece as Steganograpy [2], words, the effectiveness is the probability ofthe science of watermarking is a modern subject was detection immediately after embedding. Thisorganized developed in recent years. The first definition implies that a watermarking system mightInformation Hiding Workshop (IHW), which have an effectiveness of less than 100%.included digital watermarking as one of its primarytopic, was held in 1996. The SPIE began devoting aconference specifically to Security andWatermarking of Multimedia Contents, beginning in1999. Subsequently, up until now, there are more 840 | P a g e
  2. 2. Mr. Krunal R patel Mr .Lokesh P. Gagnani / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 1, January -February 2013, pp.840-846Fig. 1. A classification of watermarking techniques Fig. 2. General processes involved in a based on [16]. watermarking system. The watermark is encoded into the cover data in the embedding phase. AnIn general, the fidelity of a watermarking system optional encryption mechanism may also be used torefers to the perceptual similarity between the add another layer of security. In the transmissionoriginal and phase, the watermarked image can be subject towatermarked versions of the cover work. However, attack from third party. This in turns provides somewhen the watermarked work will be degraded in the challenges to the decoder to retrieve as accurate astransmission of fidelity may be more appropriate. possible the hidden data from the receivedWe define the fidelity of a watermarking system as watermarked image.the perceptual similarity between the un-watermarked and watermarked works at the point at II. RECENT ADVANCES INwhich they are presented to a consumer. WATERMARKING TECHNIQUES INData payload ratio is the ratio between the size of DIGITAL IMAGESwatermark and the size of its carrier. Different There have been many proposed novelwatermark algorithms are designed with a specific techniques to hide watermark in digital images.type of data to hide in mind. This in turns affects the These techniques can be classified into differentpayload ratio of that algorithm. Those such as in [2] categories according to several criteria [2]. The firstattempt to hide watermark inside another image, criterion is the type of domain in which the datawhile for example Digimarc, only hides a small embedding takes place. There are two major domainamount of text information. The general process types, spatial and transform domains. The secondinvolved in watermarking is criterion is according to the ability of watermark toillustrated in Figure 2. The process can be divided resist attack; fragile watermarks are ready to beinto 3 parts, Embedding, Transmission and destroyed by random image processing methods, theExtraction. change in watermark is easy to be detected, thus canIn the embedding process, the watermark may be provide information for image completeness, robustencoded into the cover data using a specific key. watermarks are robust under most image processingThis key is used to encrypt the watermark as an methods can be extracted from heavily attackedadditional protection level. The output of the watermarked image. The third criterion used toembedding process, the watermarked image, is then categorize watermark techniques is the type oftransmitted to the recipient. During this transmission information needed in the extraction process. Usingprocess, the watermarked image may be subjected to this criterion, techniques can be classified into 2attacks either deliberately or due to transmission categories; they are blind and non-blind categories.error or noise. A blind watermark system requires the cover imageTherefore, there is no guarantee that the to recover the watermarked image. On the otherwatermarked image received by the recipient is hand, a non-blind system requires nothing other thanexactly the same data as that sent by the transmitter. the watermarked image itself.This data nonetheless need to be decoded to extractthe watermarked image. In the model shown in A. Spatial DomainFigure 2, the original cover data is needed in the An analogue image can be described as aextraction process. This process is therefore called a continuous function over a two-dimensional surface.blind technique. In a non-blind technique, the The value of thisoriginal cover data is unknown to the recipient function at a specific coordinate on the latticehence the decoding process will have just rely on the specifies the luminance or brightness of the image atwatermark that location. A digital image version of this analogue image contains sampled values of the function at discrete locations or pixels. These values are said to be the representation of the image in the 841 | P a g e
  3. 3. Mr. Krunal R patel Mr .Lokesh P. Gagnani / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 1, January -February 2013, pp.840-846spatial domain or often referred to as the pixel most commonly used in image watermarking. Theydomain. Spatial embedding inserts message into are Discrete Fourier Transform (DFT), Discreteimage pixels. The oldest and the most common used Cosine Transform (DCT) and Discretemethod in this category is the insertion of the Wavelet Transform (DWT).watermark into the least significant bits (LSB) ofpixel data [2][5][6]. The embedding process of the Discrete Fourier TransformLSB technique can be illustrated as follows: Fourier Transform (FT) is an operation thatConsider that the system is required to hide a transforms a continuous function into its frequencywatermark number 178 in a 2x2 gray-scale (8-bit) components. The equivalent transform for discreteimage. Let’s assume that the image pixels are 234, valued function requires the Discrete Fourier222, 190 and 34. In an 8-bit binary format the Transform (DFT). In digital image processing, thenumber 178 is represented as 10110010. Since there even functions that are not periodic can beare 4 pixels that can be used to store this data we expressed as the integral of sine and/or cosinecan easily decide to embed pairs of bits of the multiplied by a weighing function. This weighingwatermark to the last 2 insignificant bits of the function makes up the coefficients of the Fourierpixels. The process therefore modifies the original Transform of the signal. Fourier Transform allowsbits from 11101010, 11011110, 10111110 and analysis and processing of the signal in its frequency00100010 to 11101010, 11011111, 10111100 and domain by means of analyzing and modifying these00100010 respectively. In decimal representation the coefficients.watermarked image has pixel values of 234, 223, In their paper, Ganic proposed a watermark188 and 34. algorithm based on DFT [7]. This paper describes aSince the modification of pixel values occurs in the new circularLSB of the data, the effect to the cover image is watermark scheme that embeds one watermark inoften visually indifferent. This effect however lower frequencies and another in higher frequenciesbecomes more apparent as more bits are used to hide components of the cover image. The circularlythe watermark. symmetric watermark is embedded in DFT domainOne of the major limitations in spatial domain is the by considering the magnitude of DFT coefficient ofcapacity of an image to hold the watermark. In the the cover image, the scaling factor and the circularcase of watermark. The paper presented extensiveLSB technique, this capacity can be increased by experimental results to show the performance of theusing more bits for the watermark embedding at a proposed technique given a number of attacks andcost of higher detection rate. On the other hand shows that by embedding the watermark in bothcapacity can also be improved by means of lossy frequency groups can increase the robustness of theembedding the watermark. In the latter approach, watermarking system. Pereira et. al. proposed athe watermark is quantized before the embedding method for copyright protection by embedding aprocess. Improving this limitation seems to be one digital watermark in the DFT domain [9]. Theof the major drives in spatial domain research. properties of this technique based on polar maps forThe problem of improving payload is also addressed theby El-Emam [17]. In his paper, he proposed a accurate and efficient recovery of the template in antechnique that is claimed to be able to hide images image which has undergone a general affinewhich size is as large as 75% of the cover image. transform. In this technique, the watermark isThis is achieved partly due to the application of a composed of 2 parts: one is a template whichcompression algorithm to compress the watermark contains no information in itself but can detect anyprior to embedding it. The embedding process transformations undergone by the image, andinvolves segmentation and filtering of the cover another one is a spread spectrum message thatimage to reduce the number of color. It then uses contains the hidden information. The length of thewhat it terms Main Case and Sub Case concept to hidden information is supposed to be short and it isselect the best pixels to embed the compressed subjected to a preprocessing algorithm to producewatermark. the new message of length. Prior to embedding the hidden message, the luminance component of theB. Transform Domain cover image is extracted and is used to calculate the Transform domain embeds a message by DFT coefficients. The hidden data and the templatemodifying the transform coefficients of the cover are then embedded in these coefficients. Themessage as opposed to the pixel values. Ideally, template is embedded along 2 lines in the covertransform domain has the effect in the spatial image which go through the origin and its purpose isdomain of apportioning the hidden information to detect any attacks (transformation) the image hasthrough different order bits in a manner that is undergone.robust. There are a number of transforms that can beapplied to digital images, but there are notably three 842 | P a g e
  4. 4. Mr. Krunal R patel Mr .Lokesh P. Gagnani / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 1, January -February 2013, pp.840-846Discrete Cosine Transform Wavelet Transform is a modern technique frequently Discrete Cosine Transform is related to used in digital image processing, compression,DFT in a sense that it transforms a time domain watermarking etc. The transforms are based onsignal into its frequency small waves, called wavelet, of varying frequencycomponents. The DCT however only uses the real and limited duration. A wavelet series is aparts of the DFT coefficients. In terms of property, representation of a square-integrable function by athe DCT has a strong "energy compaction" property certain orthonormal series generated by a wavelet.[14] and most of the signal information tends to be Furthermore, the properties of wavelet couldconcentrated in a few low-frequency components of decompose original signal into wavelet transformthe DCT. The JPEG compression technique utilizes coefficients which contains the position information.this property to separate and remove insignificant The original signal can be completely reconstructedhigh frequency components in images. by performing Inverse Wavelet Transformation onSrayazdi [19] proposed a blind gray-level these coefficients.watermarking scheme by dividing the cover image Watermarking in the wavelet transform domain isinto 4x4 non-overlapping blocks. The technique first generally a problem of embedding watermark in theestimates the first five DCT coefficients of each subbands of the cover image. There are fourblock in a zigzag order. It then embeds a gray-level subbands created at the end of each level of imagevalue of the watermark data by replacing each low wavelet transformation: they are Low-Low passfrequency DCT value in the central block with its subband (LL), High-Low (horizontal) subbandestimated modified values. In [20], the author (HL), Low-High (vertical) subband (LH) and High-created a new robust hybrid non-blind watermarking High (diagonal) pass subband (HH). Subsequentscheme based on discrete cosine transform (DCT) level of wavelet transformation is applied to theand Singular Value Decomposition (SVD). In this LL subband of the previous one. Figure 3 illustratesmethod, after applying the DCT in the cover image, the subband decomposition of an image using 2Dthe DCT coefficients are mapped in zigzag order waveletinto 4 transform after 2 levels of decomposition. [11] Inquadrants, which represent frequency bands from 2007, another novel technique was invented forthe lowest to the highest. SVD is then applied to robust wavelet-based watermarking [12]. The maineach quadrant. The same process is also applied to idea of this paper embeds the signature data to thethe watermark. The technique then modifies the selected group of wavelet transform coefficients,singular values in each quadrant to obtain a set of varying the watermark strength according to themodified DCT coefficients. The decoding process subband level and the group where theinvolves mapping the modified DCT coefficient corresponding coefficients reside. Initially, the inputback to their original positions and applying the image decompose into 4 levels by DWT, so we getinverse equation to produce watermarked cover approximation subbands with low frequencyimage. component and 12 detail subbands with highIn [10], a watermarking algorithm based on low frequency component. Next, the author detect edgeluminance smooth blocks in compressed DCT in each component by using Sobel edge detector, sodomain is proposed. The watermark is embedded by it is forming 2 groups of coefficients, at thesetting the sign of a subset of low- frequency DCT meanwhile, morphological dilation capture thecoefficients in these smooth blocks. In this coefficients that near the edge for forming anotheralgorithm, DCT is applied to a set of 8x8 pixel group. In the end, the watermark energy distributeblocks. The DCT takes such a signal as its input and among these groups with a variable strength.decomposes into 64 orthogonal basis signals. Thequantized DC and the AC coefficients denote theaverage luminance and the different frequency bankof a block which could reflect its texturerespectively. Firstly, the appropriate low luminancesmooth blocks should be selected based on DC andAC coefficient.Then the coefficients are quantized in zigzag order.These DCT coefficients are then modified accordingto somerobustness measure and the watermarking Fig. 3. Subbands created after two levels of Discreteinformation. The process is repeated until a desired Wavelet Transformation of an image.number of smooth blocks are embedded withwatermarks. A novel blind image watermark scheme is developed based on discrete wavelet transform inDiscrete Wavelet Transform 2007 [13]. In this 843 | P a g e
  5. 5. Mr. Krunal R patel Mr .Lokesh P. Gagnani / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 1, January -February 2013, pp.840-846paper, the author point is to make the watermark transform based method along with various imagerobust and transparent; the watermark is embedded processing operationsin the average of wavelet blocks that is smallerchange than individual coefficient to make III (A) APPROXIMATE OUTPUTwatermark more robust and concealed by using thevisual model based on the human visual system. The (a) original imageprocess first defines the average of wavelet block bythe length and width of wavelet block and n LSB ofwavelet coefficient, and then determine adjustingaverage by the n LSBs of ith wavelet coefficient inthe kth wavelet block, so that the watermarkconsisting of a binary pseudo random sequence isembedded by adjusting the average of waveletblocks bysuitable formula.III. PROPOSED WORK Usage of digital media has witnessed awonderful growth during the last decades, as a resultof their notable benefits in efficient storage, ease ofmanipulation and transmission. In the last five yearsthe protection of digital information has receivedsignificant attention within the digital media (b)watermark imagecommunity, and a number of techniques that try toaddress the problem by hiding appropriateinformation (e.g. copyright or authentication data) K.R.PATELwithin digital media have been proposed. ImageSecurity persists in many operational contexts till up (C)OUTPUT IMAGE USING INVISIBLEthis day: an encrypted e-mail message between an WATERMARKING:employee of a defines contractor and the embassy ofa aggressive power, for example, may have obviousimplications. So the study of communicationssecurity includes not just encryption but also trafficsecurity, whose essence lies in hiding information.Data information hiding is a multidisciplinarydiscipline that combines image and signalprocessing with cryptography, communicationtheory, coding theory, signal compression, and thetheory of visual and audio perception. One of themore interesting sub discipline of informationhiding is steganography. Differently fromcryptography that is about protecting the content ofmessages steganography is about concealing theirexistence, i.e. hiding information in otherinformation.Several techniques to hide information arepresented, terminology and possible related attacks,with specific attention on steganographic and IV. CHALLENGES IN WATERMARKINGcopyright schemes. In our major work describes a There are four criteria that can be used to measure the performance of an information hidingwatermark embedding technique for images using system. They arediscrete fractional Fourier transform. The idea is thata 2D discrete fractional Fourier transform of the invisibility, robustness or security, payload ratio andimage is computed, the robust watermark and fragile computational cost. From the observation of thewatermark embed in the fractional Fourier transform current watermarking systems, it can be seen that some of(FRFT) domain of the image, and the watermark these criteria are less satisfied than others.position and the transform order are used as theencryption keys. Our proposed results indicate the The first criterion is invisibility. A watermarkingembedded watermark is perceptually invisible and system is of no use if it distorts the cover image torobust also compare with the discrete Fourier the point of being useless, or even highly 844 | P a g e
  6. 6. Mr. Krunal R patel Mr .Lokesh P. Gagnani / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 1, January -February 2013, pp.840-846distracting. Ideally the watermarked imaged should several categories depending upon the domain inlook indistinguishable from the original even on the which the hidden data is inserted, the size of thehighest quality equipment. hidden data and the requirement of which theThe second criterion which is often overlooked hidden data is to be extracted.The experimentwhen assessing system performance is robustness. shows the different effective algorithms ofRobust watermark. The result indicates frequency domainwatermarking systems are expected to withstand is more robustness than spatial domain. Severaldifferent kind of attacks. Image compression, challenges that are often un-addressed in theintroduction of noise, low pass filtering, and image literature have also been identified. Meeting theserescaling, cropping, rotation are some but a few of challenges is essential in advancing the currenttypes of attacks that often are not addressed in most state of the art of watermarking in digital images.literatures. Both pixel domain and transform domainwatermarking techniques share the same level of REFERENCESexposure to these attacks. There are a few tools thatcan be used to measure a system robustness level, [1]. Petitcolas, F. A. P., Anderson, R. J.: Kuhn, M.e.g., Stirmark. Many of the proposed watermarking G., Information Hiding – A Survey,techniques aim at hiding data with large size. These Proceedings of the IEEE, Special Issue ontechniques manage to hide image as large as, or Protection of Multimedia Content, 1062-1078,even larger than, the cover image. July 1999.Although this is impressive in its own right, very [2]. Cox, I., Miller, M., Bloom, J., Fridrich, J.,little discussion and analysis is given to what extent Kalker, T.: Digital Watermarking andthis feature can be used to bring together Steganography, 2Nd Ed. ISBN: 978-watermarking with image compression techniques. 0123725851Digital images are often transmitted over the [3]. Pfitzmann, B.: Information Hidinginternet in compressed format. Being able to Terminology, Information Hiding, Firstseamlessly incorporate watermarking algorithm into International Workshop, 1174, 1996image compression system would be a challenge for [4]. Marvel, L. M., Hartwig, G. W., Boncelet, C.:researchers. Compression- Compatible Fragile and Semi-The fourth criterion that is often overlooked is the Fragile Tamper Detection, Proc. SPIE, vol.computational cost of the encoding and decoding 3971, 131—139processes. [5]. Wang, R. Z., Lin, C. F., Lin, J. C.: ImageThe computational cost determines how fast the hiding by optimal LSB substitution andtechnique can be executed and how many resources genetic algorithm, Pattern Recognition, vol.required to do so. Although this criterion is probably 34, 671- 683, 2003.considered the least important by research [6]. Swanson, M. D., Kobayashi, M., Tewfik,, it is nonetheless a significant factor to H.: Multimedia Data- Embedding andconsider when the technique is deployed as a watermarking Technologies, Proc. IEEE, vol.commercial product. 86, 1064 – 1087, 1998Figure 6 shows tradeoffs between robustness, [7]. Ganic, E., Eskicioglu, A. M.: A DFT-Basedinvisibility and capacity, a good watermarking Semi-Blind Multiple Watermarking Schemesystem should balance these three variables.. For Images [8]. Youail, R. S., Khadhim, A-K. A-R., Samawi, V. W.: Improved Stegosystem Using DFT with Combined Error Correction and Spread Spectrum, Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference, 1832-1836, 2007 [9]. Pereira, S., Pun, T.: Robust Template Matching for Affine Resistant Image Watermarks, IEEE Transactions on Image Processing, vol.9, 1123-1129, 2000. [10]. Zhou, H.T., Qi, C., Gao, X. C.: Low Fig. 6. Tradeoffs between robustness, invisibility Luminance Smooth Blocks Based and capacity [18] Watermarking Scheme in DCT Domain, Communications, Circuits and Systems V. CONCLUSION Proceedings, 2006 International Conference, In this paper we have presented description vol. 1, 19-23, 2006and analysis of recent advances in watermarking indigital images. These techniques are classified into 845 | P a g e
  7. 7. Mr. Krunal R patel Mr .Lokesh P. Gagnani / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 1, January -February 2013, pp.840-846[11]. Tao, P. N., Eskicioglu, A. M.: A robust multiple watermarking scheme in the Discrete Wavelet Transform domain, Internet Multimedia Management System Conference, vol. 5601, 133-144,2004# [12]. Ellinas, J. N.: A Robust Wavelet-based Watermarking Algorithm Using Edge Detection, Proceedings of World Academy of Science, Engineering and Technology, vol. 25, 438-443, 2007[13]. Jin, C., Pan, L-G., Su, T.: Image Watermark using Visual Model Based Discrete Wavelet Transform, IJCSES International Journal of Computer Sciences and Engineering System, vol.1, 119-124, April 2007[14]. K. R. Rao and P. Yip.: Discrete Cosine Transform: Algorithms, Advantages, Applications (Academic Press, Boston, 1990).[15]. Chang, C.C., Hsial, J.Y., Chiang, C.L: An Image Copyright Protection Scheme Based on Torus Automorphism. First International Symposium, 2002[16]. Serdean C.V: Spread Spectrum-Based Video Watermarking Algorithms for Copyright Protection. PhD thesis, university of Plymouth, 2002[17]. Nameer, N. E.: Hiding a Large Amount of Data with High Security Using Steganography Algorithm, Journal of Computer Science, 223- 232, 2007[18]. Zain, J. Clarke, M: Security in Telemedicine: Issues in Watermarking Medical Images, SETIT 2005, 3rd International Conference: Science of Electronic, Technologies of Information and Telecommunications, 2005[19]. Saryazdi, S., Demehri, M.: A Blind DCT Domain Digital Watermarking, 3rd International Conference: Sciences of Electronic, Technologies of Information and Telecommunications, 2005[20]. Sverdlov, A., Dexter, S., Eskicioglu, A. M.: Robust DCT-SVD Domain Image Watermarking for Copyright Protection: Embedding Data in all Frequencies, International Multimedia Conference, Proceedings of the 2004 workshop on Multimedia and security, 166-174, 2004 846 | P a g e