national conference on “advanced technologies in computing … · comparative study on different...

National Conference on “Advanced Technologies in Computing and Networking"-ATCON-2015Special Issue of International Journal of Electronics, Communication & Soft Computing Science and Engineering, ISSN: 2277-9477

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Comparative Study on Different Techniques of Digital ImageWatermarking

Rasika A.Harne Aarti D.Sayande Prof.N.V.Wankhade Sneha D.Ajmire

Abstract —This paper discribes recent advances inwatermarking techniques in digital images. Digitalwatermarking is a process of embedding information into digitalmedia such as image, audio, video. This paper describes variouswatermarking techniques and comparative analysis of algorithmwith their advantages and disadvantages and the techniques areclassified on the basis of different domains in which data isembedded. It starts with overview, techniques, methods and acomparative analysis of some major watermarking techniques.

Key Words —digital watermarking, discrete cosine transform(DCT), discrete wavelet transforms (DWT), least significantbit(LSB), discret fourier transform(DFT), Texture mapping codingtechnique, Patchwork algorithm, correlation-based technique.

I. INTRODUCTION

An aim of Digital image Watermarking is to add someinformation into original image to provide security.Steganography is the technique of hiding confidential informationwithin any media. From steganography a technique ofauthorization is evolved called watermarking, is the process thatembeds data called a watermark, tag or label into a multimediaobject such that watermark can be detected or extracted[1].

Digital watermarking is a way of hiding a secret or personalmessage to provide copyrights and the data integrity.The concept of digital watermarking is also associated with thesteganography. It is defined as covered writing, which hides theimportant message in a covered media, It is a new approachwhich is suitable for medical, military, and archival basedapplications. The embedded watermarks are difficult to removeand typically imperceptible, could be in the form of text, image[5].The insertion of multiple watermarks to trace a document during

its lifecycle is a very interesting and challenging application.Watermarking and cryptography techniques aim at guaranteeingthe integrity and the authentication constraints of multimediadata. In particular the former is suitable for copyright protectionpurposes thanks to the invisibility requirement: hidden marksextend some information that may be considered attributes of thecover data such as copyright[4][8]. In order to increase datasecurity, the scientific community started focusing on thepossibility of merging watermarking and encryption procedures.Watermarking is the method to hide the secret information intothe digital media using some strong and appropriate algorithm.Algorithm plays a vital role in watermarking as, if the usedwatermarking technique is efficient and strong then thewatermark beingembedded using that technique cannot be easily detected.

the algorithm otherwise it is critical to know the watermark.There are various algorithms present in the today scenario that areused to hide the information [3].

Digital watermarking is the embedding of signal, secretinformation (i.e. Watermark) into the digital media such as image,audio and video. Watermarking is used for following reasons,Proof of Ownership (copyrights and IP protection), CopyingPrevention, Broadcast Monitoring, Authentication, DataHiding.Watermarking consists of two modules watermarkembedding module and watermark detection and extractionmodule[6]. Digital watermarking technology has manyapplications in protection, certification, distribution, anti-counterfeit of the digital media.In fact, due to their lack of protection after the decryption phase,encrypted messages need an additional security level in order tokeep control on them. Vice versa, one may want to check thepresence of a mark without deciphering the data. Therefore, thechallenging goal seems to be the achievement of both levels ofprotection simultaneously and the possibility of watermarkingencrypted data and detecting the mark before and after decryption[7].This algorithm extracts multiple features from the image waveletdomain, and the watermarks are generated by the image features.The watermarks cooperate mutually to complete tampering

location, and distinguish incidental modificatio experienced byimage. The watermark generation and embedding for a image arecarried out through the image itself. No original image or anyadditional information related to watermark is needed whenauthenticating image contents, which enhances the safety andsecrecy of watermark.

WATERMARKING TECHNIQUES

Watermarking is the method used to hide the secret informationinto the digital media using some strong and appropriatealgorithm. Algorithm plays a vital role in watermarking because ifthe used watermarking technique is efficient and strong then thewatermark being embedded using that technique cannot be easilydetected. The attacker can only destroy or detect the secretinformation if he know the algorithm otherwise it is critical toknow the watermark. There are various algorithms present intoday’s scenario that are used to hide the information. Thosealgorithms come into two domains, Spatial and Frequencydomain.According to domain: Spatial domain: This domain focuses onmodifying the pixels of one or two randomly selected subsets ofimages. It directly loads the raw data into the image pixels. Someof its algorithms are LSB, SSM Modulation based technique.Frequency domain: This technique is also called transform


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domain. Values of certain frequencies are altered from theiroriginal. There are several common used transform domainmethods, such as DCT, DWT, and DFTa)Spatial domain:

Spatial domain digital watermarking algorithms directly load theraw data into the original image. Spatial watermarking can also beapplied using color separation. In this way, the watermark appearsin only one of the color bands. This renders the watermark visiblysubtle such that it is difficult to detect under regular viewing.Spatial domain is used in manipulating or changing an imagerepresenting an object in space to enhance the image for a givenapplication. Techniques are based on direct manipulation ofpixels in an image . Some of its algorithms are as discussedbelow:

1. Texture mapping coding Technique:This method is useful in only those images which have some

texture part in it. This method hides the watermark in the texturepart of the image. This algorithm is only suitable for those areaswith large number of arbitrary texture images (disadvantage), andcannot be done automatically. This method hides data within thecontinuous random texture patterns of a picture.

2. Patchwork Algorithm:Patchwork is a data hiding technique developed by Bender et aliiand published on IBM Systems Journal, 1996[11]. It is based on apseudorandom, statistical model. Patchwork imperceptibly insertsa watermark with a particular statistic using a Gaussiandistribution. A pseudo randomly selection of two patches iscarried out where the first one is A and the second is B. Patch Aimage data is brightened where as that of patch B is darkened (forpurposes of this illustration this is magnified). The following arethe steps involved in the Patchwork algorithm:» Generate a pseudo-random bit stream to select pairs of pixelsfrom the cover data.» For each pair, let d be the difference between the two pixels.» Encode a bit of information into the pair. Let d < 0 represent 0and d > 0represent that the given pixels are not ordered correctly,swap them.» In the event that d is greater than a predefined threshold or if isequal to 0, ignore the pair and proceed to the next pair.» Patchwork being statistical methods uses redundant patternencoding to insert message within an image.3. Correlation-Based Technique:In this technique, a pseudorandom noise (PN) pattern say W(x, y)is added to cover image I(x, y). Iw(x, y) = I(x, y) + k*W(x, y)Where K represent the gain factor, Iw represent watermarkedimage at position x, y and I represent cover image. Here, if weincrease the gain factor then although it increases the robustnessof watermark but the quality of the watermarked image willdecrease.b) Frequency domain:

This technique is also called transform domain. Values of certainfrequencies are altered from their original. There are severalcommon used transform domain methods, such as DCT, DWT,and DFT.

Least Significant Bit: Old popular technique embeds thewatermark in the LSB of pixels. This method is easy toimplement and does not generate serious distortion to the image.The embedding of the watermark is performed choosing a subsetof image pixels and substituting the least significant bit of each ofthe chosen pixels with watermark bits. The watermark may bespread throughout the image or may be spread in the selectedlocations of the image. The principle of embedding is fairlysimple and effective. If we use a grayscale bitmap image, whichis 8- bit, we would need to read in the file and then add data to theleast significant bits of each pixel, in every 8-bit pixel. In agrayscale image each pixel is represented by 1 byte consist of 8bits. It can represent 256 gray colors between the black which is 0to the white which is 255. The principle of encoding uses theLeast Significant Bit of each of these bytes, i.e. the bit on the farright side. If data is encoded to only the last two significant bits(which are the first and second LSB) of each color component itis most likely not going to be detectable; the human retinabecomes the limiting factor in viewing pictures. For the sake ofthis example only the least significant bit of each pixel will beused for embedding information. If the pixel value is 138 whichis the value 10000110 in binary and the watermark bit is 1, thevalue of the pixel will be 10000111 in binary which is 139 indecimal. In this example we change the underline pixel [10].

Discrete cosine transforms (DCT): DCT represents data interms of frequency space rather than an amplitude space. This isuseful because that corresponds more to the way humans perceivelight, so that the part that are not perceived can be identified andthrown away. DCT based watermarking techniques are robustcompared to Spatial domain techniques Such algorithms arerobust against simple image processing operations like lowpasspass filtering, brightness and contrast adjustment, blurringetc. However, they are difficult to implement and arecomputationally more expensive. At the same time they are weakagainst geometric attacks like rotation, scaling, cropping [9].

Discrete wavelet transforms (DWT):Wavelet Transform is a modern technique frequently used indigital image processing, compression, watermarking etc. Thetransforms are based on small waves, called wavelet, of varyingfrequency and limited duration. The DWT (Discrete WaveletTransform) separates an image into a lower resolutionapproximation image (LL) as well as horizontal (HL), vertical(LH) and diagonal (HH) detail components. The Discrete WaveletTransform (DWT) is currently used in a wide variety of signalprocessing applications, such as in audio and video compression,removal of noise in audio, and the simulation of wireless antennadistribution. Wavelets have their energy concentrated in time andare well suited for the analysis of transient, time-varying signals.Since most of the real life signals encountered are time varying innature, the Wavelet Transform suits many applications very well .One of the main challenges of the watermarking problem is toachieve a better tradeoff between robustness and perceptivity.Robustness can be achieved by increasing the strength of theembedded watermark, but the visible distortion would beincreased as well. However, DWT is much preferred because it


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provides both a simultaneous spatial localization and a frequencyspread of the watermark within the host image [7] .The basic ideaof discrete wavelet transform in image processing is to multi-differentiated decomposition of the image into sub-image ofdifferent spatial domain and independent frequencies.

Advantages of DWT over DCT: Wavelet transform understandsthe HVS more closely than the DCT. Wavelet coded image is amulti-resolution description of image. Hence an image can beshown at different levels of resolution and can be sequentiallyprocessed from low resolution to high resolution.

Disadvantages of DWT over DCT: Computational complexityof DWT is more compared to DCT. As Feig (1990) pointed out itonly takes 54 multiplications to compute DCT for a block of 8x8,unlike wavelet calculation depends upon the length of the filterused, which is at least 1 multiplication per coefficient.

b) Discrete Fourier transforms (DFT):Transforms a continuous function into its frequency components.It has robustness against geometric attacks like rotation, scaling,cropping, translation etc. DFT shows translation invariance.Spatial shifts in the image affects the phase representation of theimage but not the magnitude representation. Circular shifts in thespatialdomain don't affect the magnitude of the Fourier transform.Advantages of DFT over DWT and DCT: DFT is rotation,

scaling and translation (RST) invariant. Hence it can be used torecover from geometric distortions, whereas the spatial domain,DCT and the DWT are not invariant and hence it is difficult toovercome from geometric distortions..b) Frequency domain:

This technique is also called transform domain. Values of certainfrequencies are altered from their original. There are severalcommon used transform domain methods, such as DCT, DWT,and DFT.

Least Significant Bit: Old popular technique embeds thewatermark in the LSB of pixels. This method is easy toimplement and does not generate serious distortion to the image.The embedding of the watermark is performed choosing a subsetof image pixels and substituting the least significant bit of each ofthe chosen pixels with watermark bits. The watermark may bespread throughout the image or may be spread in the selectedlocations of the image. The principle of embedding is fairlysimple and effective. If we use a grayscale bitmap image, whichis 8- bit, we would need to read in the file and then add data to theleast significant bits of each pixel, in every 8-bit pixel. In agrayscale image each pixel is represented by 1 byte consist of 8bits. It can represent 256 gray colors between the black which is 0to the white which is 255. The principle of encoding uses theLeast Significant Bit of each of these bytes, i.e. the bit on the farright side. If data is encoded to only the last two significant bits(which are the first and second LSB) of each color component itis most likely not going to be detectable; the human retinabecomes the limiting factor in viewing pictures. For the sake ofthis example only the least significant bit of each pixel will be

used for embedding information. If the pixel value is 138 whichis the value 10000110 in binary and the watermark bit is 1, thevalue of the pixel will be 10000111 in binary which is 139 indecimal. In this example we change the underline pixel [10].

Discrete cosine transforms (DCT): DCT represents data interms of frequency space rather than an amplitude space. This isuseful because that corresponds more to the way humans perceivelight, so that the part that are not perceived can be identified andthrown away. DCT based watermarking techniques are robustcompared to Spatial domain techniques Such algorithms arerobust against simple image processing operations like lowpasspass filtering, brightness and contrast adjustment, blurringetc. However, they are difficult to implement and arecomputationally more expensive. At the same time they are weakagainst geometric attacks like rotation, scaling, cropping [9].

Discrete wavelet transforms (DWT):Wavelet Transform is a modern technique frequently used indigital image processing, compression, watermarking etc. Thetransforms are based on small waves, called wavelet, of varyingfrequency and limited duration. The DWT (Discrete WaveletTransform) separates an image into a lower resolutionapproximation image (LL) as well as horizontal (HL), vertical(LH) and diagonal (HH) detail components. The Discrete WaveletTransform (DWT) is currently used in a wide variety of signalprocessing applications, such as in audio and video compression,removal of noise in audio, and the simulation of wireless antennadistribution. Wavelets have their energy concentrated in time andare well suited for the analysis of transient, time-varying signals.Since most of the real life signals encountered are time varying innature, the Wavelet Transform suits many applications very well .One of the main challenges of the watermarking problem is toachieve a better tradeoff between robustness and perceptivity.Robustness can be achieved by increasing the strength of theembedded watermark, but the visible distortion would beincreased as well. However, DWT is much preferred because itprovides both a simultaneous spatial localization and a frequencyspread of the watermark within the host image [7] .The basic ideaof discrete wavelet transform in image processing is to multi-differentiated decomposition of the image into sub-image ofdifferent spatial domain and independent frequencies.

Advantages of DWT over DCT: Wavelet transform understandsthe HVS more closely than the DCT. Wavelet coded image is amulti-resolution description of image. Hence an image can beshown at different levels of resolution and can be sequentiallyprocessed from low resolution to high resolution.

Disadvantages of DWT over DCT: Computational complexityof DWT is more compared to DCT. As Feig (1990) pointed out itonly takes 54 multiplications to compute DCT for a block of 8x8,unlike wavelet calculation depends upon the length of the filterused, which is at least 1 multiplication per coefficient.

b) Discrete Fourier transforms (DFT):Transforms a continuous function into its frequency components.It has robustness against geometric attacks like rotation, scaling,


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cropping, translation etc. DFT shows translation invariance.Spatial shifts in the image affects the phase representation of theimage but not the magnitude representation. Circular shifts in thespatialdomain don't affect the magnitude of the Fourier transform.Advantages of DFT over DWT and DCT: DFT is rotation,

scaling and translation (RST) invariant. Hence it can be used torecover from geometric distortions, whereas the spatial domain,DCT and the DWT are not invariant and hence it is difficult toovercome from geometric distortions..

Factor affecting Watermark

1) Robustness: The watermark should be able to withstand afternormal signal processing operation such as image cropping,transformation, compression etc.

2) Imperceptibility: The watermarked image should look likesame as the Original image to normal eye.The viewer cannotdetect that watermark is embedded in it..3) Security: Unauthorized parties should not be able to read oralter the watermark. Ideally, the watermark should not bedetectable by unauthorized parties.

4) Fast embedding and/or retrieval: The speed of a watermarkembedding algorithm is important for applications wheredocuments are distributed. The large bandwidth necessary forvideo also requires fast embedding methods multiple watermarks.It may also be desirable to embed multiple watermarks in adocument. For example, an image might be marked with a uniquewatermark each time it is downloaded.

5) Unambiguity: A watermark must convey unambiguousinformation about the rightful owner of a copyright, point ofdistribution, etc.

RELATED WORK

Digital watermarking is the technology used for copy control,media identification, tracing and protecting content owner'srights. The Watermarking technique based on spatial domain wasdeveloped first. They are easy to implement and less complexspatial domain Watermarking technique called LSBwatermarking. The Least Significant Bit of the binary convertedpixel value of the host image is selected and it is replaced by thepixel of the watermark image. So that a third party cannot viewthe watermark. The watermark is embedded at the LSB of thehost image. But the spatial domain methods are considered to beless robust then the frequency domain methods were developed.The commonly used frequency domain methods are based onDCT and DWT. So that problem statement is to find out whichwatermarking algorithm. DCT and DWT is more efficient andalso to analyse the robustness of a method which is thecombination of DCT and DWT.

A comparative study on different watermarking techniques whichare DCT, DWT and DCT+DWT. In each method, the coverimage is resized into 256×256 and divided into 8×8 blocks. Onthese blocks, transformation is applied and on that the watermarkis applied and finally, inverse transformation is done.

Simple Digital watermarking is a technology in which awatermark (secret information) is hidden in the digital mediausing an appropriate algorithm for the authentication andidentification of original owner of the product. Outcome we getwatermarked image. Simple digital watermarking techniqueconsists of two modules watermark embedding module andwatermark detection and extraction module. Watermarkembedding embeds the watermark into the original image using akey. The watermark embedding module is as Fig.(b) WatermarkEmbedding Module Watermark detection and extraction moduleis used to determine whether the data contains specifiedwatermark or the watermark can be extracted.

Fig:(a)

Fig(b) Watermark embedding module

Watermark Image

Originalimage

Detectedmark

Originalmark

ExtractionEmbedding

key key


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Comparisons of Different Watermarking Techniques

Algorithm Advantages DisadvantagesLSB 1. Easy to

implement andunderstand2. Lowdegradation ofimage quality3. Highperceptualtransparency.

1. It lacks basicrobustness2. Vulnerable tonoise3. Vulnerable tocropping,scaling.

Correlation 1. Gain factorcan be increasedresulting inincreasedrobustness

1. Image qualitygets decreaseddue to very highincrease in gainfactor.

Patchwork 1. High level ofrobustnessagainst most typeof attacks.

1. It can hideonly a verysmall amount ofinformation

Texturemappingcoding

1. This methodhides data withinthe continuousrandom texturepatterns of apicture.

1.Thisalgorithmis only suitablefor those areaswith largenumber ofarbitrary textureimages

DCT 1. Thewatermark isembedded intothe coefficientsof the middlefrequency, so thevisibility ofimage will notget affected andthe watermarkwill not beremoved by anykind of attack.

1. Block wiseDCT destroysthe invarianceproperties of thesystem.2. Certainhigherfrequencycomponentstend to besuppressedduring thequantizationstep.

DWT 1. Block wisedestroys DCTthe invarianceproperties of thesystem.2. Certain higherfrequencycomponents tendto be suppressedduring thequantizationstep.

1. Cost ofcomputing maybe higher.2. Longercompressiontime. 3.Noise/blur nearedges of imagesor video frames.

DFT 1. DFT isrotation, scalingand translation(RST) invariant.Hence it can beused to recoverfrom geometricdistortions

1. Compleximplementation2. Cost ofcomputing maybe higher.

CONCLUSION

Digital watermarks have been used in the last few years to protectthe ownership of digital data. Digital watermarking can be appliedon audio, video, multimedia. As we have come to know thatwatermarking is a way to provide security by hiding informationas well as a way to prove identity and to make documentsconfidential, this scheme would be highly useful in real worldapplications. Over here we have seen different watermarkingtechniques. This technique becomes easy for all users tounderstand and to watermark their own information. Even it isrobust over attacks so this can be simple, easy and robust way ofwatermarking. In this paper we have presented description andanalysis of recent advances in watermarking in digitalimages.These techniques are classified into several categoriesdepending upon the domain in which the hidden data is inserted,the size of the hidden data and the requirement of which thehidden data is to be extracted. The result indicates frequencydomain is more robustness than spatial domain. Each of thesetechniques has its advantages and disadvantages, and each onetrades some important watermarking property for another.Watermarking is a very active research field with a lot ofapplications. Although it is a relatively new field, it has producedimportant algorithms for hiding messages into digital signals.

ACKNOWLEDGEMENT

We express our sincere gratitude to Prof.S.P.Deshpande sirworking as HOD in P.G. Department of Computer Science andTechnology, for his valuable guidance and advice. Also we wouldlike to thanks Prof.N.V.Wankhade sir as Assistant professor andour faculty members for their continuous support andencouragement. Last, but certainly not least, We would like tothank our friends and family for their care and constant support.

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steganography and watermarking”International Journal of Research in IT &Management (February 2012).

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3) Kiratpreet Singh Dhaliwal and Rajneet Kaur “Comparative study of singlewatermarking to multiple watermarking over a color image” Issue 2 March2013.

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10) technique”International Journal of Computer Science & EngineeringTechnology (IJCSET)Vol. 4 No. 02 Feb 2013.

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AUTHOR’S PROFILE

Rasika A Harne receivedher BCA in ComputerApplication from SGBAmravati University.Presently student of MScComputer Science fromHVPM an autonomouscollege.

Aarti D. Sayande receivedher BCA in ComputerApplication from SGBAmravati University.Presently student of MScComputer Science fromHVPM an autonomouscollege.

Sneha D. Ajmire receivedher BSc in ComputerScience from SGBAmravatiUniversity.Presently studentof MSc Computer Sciencefrom HVPM anautonomous college.

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