NOVATEUR PUBLICATIONS International Journal of Research Publications in Engineering and Technology [IJRPET] ISSN: 2454-7875 VOLUME 3, ISSUE 8, Aug. -2017
A CLASSICAL REVIEW ON ADVANCED DIGITAL IMAGE WATERMARKING TECHNIQUES BAISA L. GUNJAL Department of Information Technology, Amrutvahini College of Engineering, Sangamner, District Ahmednagar, Maharashtra, India, hello_baisa@yahoo.com ABSTRACT: The world has become a global village in digital era due to advances in internet and communication technology. Presently, creation, copy and transmission of image data via internet and mobile phone are very common practices. The access, sharing, replication and manipulation of medical images have become daily needs. Image data distributed can be copied repeatedly without errors putting the rights of owners at risk. Even though encrypted for distribution, images can be unprotected after decryption. Deployment of information and communication technology infrastructure is bringing revolution to health industry. Consequently, worldwide e-health technology and associated standards demand strong security of medical image data. Digital image data security is achieved by different ways.Digital image watermarking provides copyright protection and authentication by hiding ownership information in image data. This paper presents motivation along with vast number of application area of digital image watermarking. The paper mainly focuses on classical review of variety of advanced image watermarking techniques. The paper recommends transform domain image watermarking for strong provision of imperceptibility, robustness and security. This study also draws some significant conclusions based on classical review of advanced image watermarking techniques. KEYWORDS: Watermarking, PSNR, Fingerprinting, MMS, Shift-variant, EVM, Compression. I. INTRODUCTION: Digital image watermarking protects the rights of their owners in variety of ways including copyright identification, user identification or fingerprinting (FP), authenticity determination, automated monitoring and copyright protection. Digital fingerprinting is used to trace out unauthorized user and identify the copyright violator. This is achieved by embedding a fingerprint in each copy to be distributed so that authorized user can be identified.With advances in communication technology and due to widespread use of internet and mobile phones, image data security is essentially required in many applications areas [1][2].
Image copyright communication for digital rights management (DRM) and protection strongly demands it. Multimedia Message Service (MMS) are commonly used to send images through mobile phones where security is required. Central Bureau Investigations (CBI) and other crime investigation agencies need to transmit either grey scale or color criminal images to distant officesvia internet or cell phones. Such image data demands high safety and confidentiality. ‘Secured Voting System’ is heart of democratic countries worldwide. E-voting systems are better options for Electronic Voting Machines (EVM) for implementation of free and fair voting system which is also cost effective as it saves extra financial burden caused economy system of a given country.Biometric based watermarking techniques can be efficiently used for evoting systems used in parliament, president and municipal elections. Biometric based watermarking techniques can be efficiently used for e-voting systems used in parliamentary, presidential or municipal. Distance education is growing rapidly nationwide or worldwide. Due to shortage of highly qualified skillful human resources in rural and backward areas intelligent technologies for distant learning with student-teacher interaction is required with secured transmission of image data. Here, digital image watermarking can provide solution. Many Android based application in mobile phones are written using Java Programming language. Since mobile phones are capable of running Java programs, even simple program can extract hidden messages from innocent images. Hence, watermarking techniques are equally used for all types of mobile based image data security. Secured image databases required by health insurance companies and car insurance companies during decision making process of accidental cases and allowances of damaged vehicles. The banking services including multinational companies require for maintaining secure image databases and their transmission, secured passport IDs require secured authentication for customer-image data during transmission to and from central administrative offices. The generalized approaches and analysis used for image data can be easily applied for other media such as audios and videos . In telemedicine for number healthcare applications like teleradiology, telepathy, telecare, telesurgery, teleneurology medical images needproper safetyand
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NOVATEUR PUBLICATIONS International Journal of Research Publications in Engineering and Technology [IJRPET] ISSN: 2454-7875 VOLUME 3, ISSUE 8, Aug. -2017 confidentiality because patient diagnosis by specialists is between original watermark and extracted watermark. i.e. based on information containedin medicalimages. Many ‘correlation factor’. times patient who is criticallyill or seriously injured in accident need to be treated locally by effective and secured C. CAPACITY: communicationof EPR (Electronic Patient Report) data It is measure of number of bits those can be embedded between remote hospitals and distant specialty hospitals. in a cover image. A good quality watermarking technique Clinical Decision Support System (CDCS) extract should have maximum embedding capacity. Transparency knowledge from electronic medical records (EMR) and and robustness to image processing conflict with each provide input to the doctors those do exact diagnosis. The other under high payload scenario. The high capacity transmission of medical images from remote hospitals to watermark embedding can be achieved by compromising specialist hospital located at distant geographical locations either perceptual quality or robustness of watermarking is common practice now a day. Sensitive medical images technique. Thus, it is the fundamental problem to achieve need ‘a priori’ and ‘a posteriori’protection. Hence,secure, suitable tradeoff between fidelity and robustness. robust and high capacity watermarking techniques is demand of healthcare industry. A medical image contains D. SECURITY: Region of Interest (ROI) and Region of Non Interest It is the ability of preserving owner’s rightful (RONI). ROI is sensitive region of medical image using information. The watermarking technique should be which doctors do exact diagnosis and decide treatment complex enough to break. It measures resistance of according. So, ROI should not be disturbed while watermark in case attacker attempts to various image like embedding watermark. Hence, ROI based watermarking of rotation, scaling, noise addition, noise filtering, resizing, digital images need to be handled carefully. cropping, collision attacks, compression. Robustness depends on different factor such as watermark hiding II. IMAGE QUALITY METRICS: capacity, strength and visibility. It is measured in terms of Imperceptibility, robustness, payload and security are correlation between original watermark and extracted four attributes those determine quality of image watermark. i.e. ‘correlation factor’. watermarking scheme. III. CLASSICAL REVIEW: A. IMPERCEPTIBILITY OR PERCEPTUAL The numbers of watermarking techniques have been TRANSPARENCY: proposed by researchers for grey scale, color and medical The imperceptibility is also called as perceptual images. According to embedding domain watermarking transparency or fidelity. Addition of watermark in a cover techniques are categorized as spatial domain and image is as good as addition of noise to it. Hence, the transform domain. imperceptibility of watermarked image is degraded during watermark embedding process. Imperceptibility of the A. SPATIAL DOMAIN TECHNIQUES: watermarked image is measured in term of various Least Significant Bit (LSB) based techniques are attributes like difference based measures such as Peak examples of spatial domain techniques which are less signal to noise ratio(PSNR) which is determined in terms secured, having low watermark information hiding of mean square error(MSE). MSE, PSNR are pixel difference capacity, results less perceptual quality of watermarked based measures which compute the distortion between image and can be detected easily. Mohammed, Ghassan N two images based on their pixel wise difference. Better et al.[2] proposed Dual Intermediate Significant Bit (DISB) PSNR shows better quality of watermarked image. model to achieve robustness against possible attacks as well as perceptual quality of the watermarked images.The B. ROBUSTNESS: two bits are embedded into all pixels of the cover image Watermark must be capable for survival against both and other six bits are altered such that they will directly intentional and unintentional attacks. Robustness is assimilate the original pixel. The resultant watermarked detecting reliability of given watermarking technique in image quality is improved with compared with LSB after presence of channel noise or intentional attacks. It embedding two bits.In transform domain techniques, measures immunity of watermark against attempts to watermark is inserted into transformed coefficients of various image modification and manipulation like noise image. It gives better watermark information hiding addition, noise filtering, rotation, scaling, collision attacks, capacity and also provides better robustness against resizing, cropping, compression. Robustness depends on watermarking attacks. The frequency domain methods are various factor like watermark information hiding capacity, widely applied compared to spatial domain methods. visibility and strength. It is measured in terms of similarity 59 | P a g e
NOVATEUR PUBLICATIONS International Journal of Research Publications in Engineering and Technology [IJRPET] ISSN: 2454-7875 VOLUME 3, ISSUE 8, Aug. -2017 B. VISIBLE WATERMARKING TECHNIQUES: F. COLOR TRANSFORMATION BASED TECHNIQUES: Tsung-Yuan Liu et al.[3] presented lossless visible Soo-Chang Pei et al.[12] presented reversible color watermarking method of cover image. This method transformsfor red-green-blue(RGB) and KarhunenLoeve embeds 440x330 size watermarks with 88,424 average (KLA), RGB-IV1V2, RGB-XYZ, RGB-UVW, RGB-YIQ, nontransparent pixels and average capacity of 33.7% of RGB-DCT, RGB-YCbCr, RGB-YUV, RcGcBc and RGB-RsGsBs watermark coverage. But visible watermarking schemes with reduced implementation complexity. are used only for limited application areas. A perceptually tuned method for color images is presented by Chun-Hsien Chou et al. [13] hiding watermark into 3 C. BLIND WATERMARKING TECHNIQUES: color channels and host image without resulting A blind watermarking techniques do not require cover perceivable distortion. The method is based on CIEDE 200 image during extraction process. Md. Iqbal H. Sarker et color difference equation and Just Noticeable Difference al.[4] presented Hadamard transform and best first search (JND) model. Paulo ViniciusKoerich Borges et al.[14] based blind watermarking technique to achieve robustness proposed transparent color modulation for text data against compression, rotation, cropping, noise addition and hiding using print scan(PS) channel model. DWT based noise filtering attacks. Jiasong Wu et al.[5], also presented color image watermarking in YCbCr color space is watermarking technique for Sliding Window based presented by Shang-Lin Hsieh et al.[15] and YIQ color Sequency-Ordered Complex Hadamard Transform. The space technique is presented by Guangmin Sun et al.[16]. technique is proved faster than only FFT or the sliding DFT based methods. Feature based classification technique for G. REVERSIBLE WATERMARKING TECHNIQUES: blind Steganalysis technique is proposed by Wen-Nung Lie Reversible watermarking is special data hiding et al.[6]. Here, two statistical properties in the spatial and technique where watermark with original image are DCT domains are proposed blindly to determine the completely recovered. Such techniques are used in presence of hidden messages in image. The neural applications like medical and military where media do not classifier based on two extracted features namely gradient allow any loss. Hao-Tang Chan et al.[17] presented energy and statistical variance of the Laplacian parameters reversible fragile transform domain method based on are proposed to achieve blind steganography. digital hologram. Here the reversibility is achieved using FabrizioGuerrini et al.[7] presented blind watermarking Hadamard transform. A. Umamageswari et al.[18] scheme based on quantization index modulation(QIM). The proposed reversible watermarking technique in scheme is robust against tone mapping operators. This compression domain. Lingling An et al.[19] presented scheme is specifically presented for High dynamic range robust reversible watermarking(RRW) using wavelet (HDR) images which allow accurate rendering of wide domain statistical histogram shifting and range of luminance values. clustering(WSQH-SC) pixel wise masking to balance robustness and invisibility. D. SPREAD SPECTRUM BASED TECHNIQUES: Ioan-CatalinDragoi et al.[20] presented local prediction Fan Zhang et al.[8] presented spread spectrum based watermarking technique with four horizontal and watermarking scheme based on perceptual quality metrics. vertical grouping of four pixels. Sunil Lee et al.[21] This method is proposed as an optimization to search proposed reversible watermarking method using integer watermark to minimize distortion of watermarked image to integer wavelet transform. The mean squared distortion and maximize correlation between watermark and spread between original and watermarked images with given spectrum carrier with fast implementation. Spread payload is minimized by adaptively embedding watermark Spectrum Watermarking Scheme is presented by Minoru in a cover image. Kuribayashi et al.[9] for fingerprint application. H. HISTOGRAM BASED TECHNIQUES: E. QUANTIZATION BASED TECHNIQUES: Histogram based schemes are also presented for Mohsen Zareian et al.[10] proposed modulation based reversible watermarking. PasunuriNagarju et al.[22] quantization watermarking with adaptively selected presented histogram bin shifting based reversible quantization step size. This method found robust for watermarking for grey scale images. In range of pixels of 0AWGN attack, JPEG attack, filtering attack, salt-pepper 255, from histogram, zero point (pixel value with noise attack and rotation attack. Quantization based frequency zero) and peak point (pixel value with frequency watermarking is also presented by Xiangui Kang et al.[11] maximum) are effectively shifted for data embedding. which is robust to JPEG, noise addition, histogram GouenouCoatrieux et al.[23] proposed scheme using equalization, color reduction and Gamma correction dynamic histogram shifting which dynamically uses local attacks. specificities of local contents. 60 | P a g e
NOVATEUR PUBLICATIONS International Journal of Research Publications in Engineering and Technology [IJRPET] ISSN: 2454-7875 VOLUME 3, ISSUE 8, Aug. -2017 I. E-HEALTH CARE BASED MEDICAL WATERMARKING watermarking scheme consistent with our Human Visual TECHNIQUES: System. This scheme embeds watermark into all E-health technology and related telemedicine (luminance and chrominance) components of color images. applications including telepathy, telecare, teleradiology, The logic is based on fact that addition and subtraction of telesurgery and teleneurology demand high confidentiality two colors produce other colors. and safety of Electronic Patient Records (EPR). Medical MatthieuUrvoy et al.[33] developed image with region of interest (ROI) is need to be treated watermarking technique in Fourier domain which is carefully because doctors do exact diagnosis based on robust against geometrical distortions. The watermark information provided by ROI based medical images. Kumar embedding is done within Fourier domain by substitution M et al.[24] proposed reversible image watermarking of both the magnitude (energy) and the phase method for medical where both payload and the patient (information). Peng LUO et al.[34] proposed color image information are encrypted using symmetric key encryption watermarking technique using non sampled contourlet algorithm. GouenouCoatrieux et al.[25] proposed scheme transform (NSCT) with HVS masking technique to obtain using non-significant region watermarking with signatures high robustness and transparency. Lihong Cui et al.[35] extracted from different pixel blocks of interest. This presented multi-wavelet based adaptive scheme based on method uses set of three signatures are used for Just Perceptual Weighting(JPW) model. This model confidentiality. DalelBouslimi et al.[26] presented method includes various masking effects of HVS perception by using joint encryption/watermarking to verify reliability of considering eye sensitivity to change in noise depending medical images. This method guarantees priori and on spatial frequency, texture and luminance of image sub posteriori protection of medical images. bands. Chalamala S.R et al. [36] proposed new lightweight M. Kamran et al.[27] proposed e-health technology related and robust method image watermarking based on scheme of Electronic Medical Records(EMR) system that is contourlet transform compared its performance with a processed by Clinical Decision Support System(CDSS). This wavelet transform based method. The fixed size block of information preserving scheme is robust to insertion, sub band coefficients are obtained using contourlet deletion and alteration attacks. A novel scheme using transform and watermark bit is embedded into one of the integration of multiple cryptographic mechanisms and key Eigenvalues of that fixed size block. The authors proved management scheme is proposed by Chien-Ding Lee et that watermarking techniques using contourlettransfom al.[28] to track malicious staff members using are more robust than watermarking techniques using watermarked clue. C. Vinoth Kumar et al.[29] proposed wavelet transform under several attacks but wavelet based high embedding capacity reversible technique for medical techniques give better perpetual transparency than images. The cover image is hierarchically divided into contourlet based techniques. smaller blocks and further histogram shifting mechanism is applied for data hiding. K. WATERMARKING BASED ON COMPOSITION OF TWO TRANSFORMS: J. WATERMARKING USING SPECIAL PROPERTIES OF Some researchers combined spatial properties of SINGLE TRANSFORM: transforms giving composition of multiple transforms. The Discrete Wavelet Transform (DWT) is very similar to combined DCT-DWT based technique is proposed by Human Visual System (HVS). It allows multi-resolution KetaRaval et al.[37]. The composite DWT-DCT based decomposition of image and exact reconstruction of technique is proposed by Saied AmirgholipourKasmani et decomposed image. Hence DWT has become researchers al.[38] in which binary watermarked image is embedded in focus. Roland Kwitt et al.[30] presented DWT based spread selected sub bands of three level transformed of host spectrum blind watermarking.Discrete Cosine image. Each of DWT sub band is selected and it’s DCT Transform(DCT) has ‘energy compaction property’. Most of transform of is computed. Finally, Pseudorandom Number visually significant information of natural images is (PN) sequences of watermark bits are generated and concentrated in few coefficients of DCT. Spatio-Temporal thosePN sequencesare embedded in coefficients of related Just Noticeable distortion (JND) based scheme for grey DCT middle frequencies. Singular value decomposition scale image in DCT domain is presented by Zhenyu Wei et (SVD) gives good stability.Small modifications in singular al.[31]. This JND based scheme incorporates spatial values do not cause many variations. Hence, some of contrast sensitivity function (CSF), luminance effect, researchers have combined good properties of DWT and contrast masking effect and Gamma correction in DCT SVD. Hailiang Shi et al.[39] combined DWT and SVD domain. Experimental results show that the Spatiotransforms for rotation, scaling and translation(RST) Temporal JND model is consistent with HVS. Tsz Kin Tsui invariant scheme. The scheme is found robust for variety et al.[32] presented Fourier transform based color image of RST attacks. Priyanka Singh et al.[40] used combined 61 | P a g e
NOVATEUR PUBLICATIONS International Journal of Research Publications in Engineering and Technology [IJRPET] ISSN: 2454-7875 VOLUME 3, ISSUE 8, Aug. -2017 DWT-SVD based technique in YUV and YIQ color spaces. invisible digital watermarking technique using Particle The technique is tested with cover images of 512x512 Swarm Optimization (PSO) with SVD. Image watermarking sizefor checking perceptual transparency and robustness. system demands strongly techniques so that underlying The method demonstrated better performance of Y color system should be unbreakable. space. Chih-Chin Lai et al. [41] used DWT and SVD hybridization for achieving robustness against geometric N. WATERMARKING TECHNIQUES USING EFFECTIVE attacks, noising attacks, denoising attacks, format SCRAMBLING METHODS: compression attacks and other image processing attacks. Many researchers have used variety of scrambling Redundant Discrete Wavelet Transform (RDWT) is methods to provide security. Watermark scrambling variation of DWT to overcome shift-variant limitation of methods are used to convert image into unrecognizable DWT which occurs due to down sampling process after patterns so that extracted watermark cannot be each level of filtering that causes significant change in recognized directly. Fibonacci transform, Fibonacci Q wavelet coefficient. Samira Lagzian et al.[42] presented transform, Arnold transform, modified Arnold transform, RDWT-SVD based method that embeds data in all LL,LH,HL Lucas transform, Fibonacci-Lucas transform with their and HH sub bands of DWT. The scheme found robust comparative sustainability against robustness is presented against rotation attack, Gaussian noise, salt & pepper by Minati Mishra et al.[50], grey code transformation, attack, speckle noise attack, median filtering attack and affine modular transformation are also proposed by histogram equalization attack.The composition of DWTEhsanNezhadarya et al.[51].An excellent style manual for DFT isused by Xiangui Kang et al.[43] for achieving science writers is [7]. robustness against different affine transforms and compression attacks. IV. DISCCUSSIONS AND CONCLUSIONS: Based on the classical review presented here, some L. WATERMARKING BASED ON COMPOSITION OF TWO significant conclusions are drawn here: TRANSFORMS: The highly secured, strongly robust with high payload The composition of three transforms is also used by watermarking techniques for grey scale, color and some of researchers. SivavenkateswaraRao. V et al.[44] medical images are required in majority application combined DWT,DCT and SVD for optimization of areas of image processing. robustness and fidelity. The scheme is tested for attacks The spatial domain image watermarking techniques including Gaussian noise(σ=0.01), rescaling (512-1024are simple for implementation but support less 512), histogram equalization, gamma correction (0.7), low watermark information hiding capacity, poor pass filtering, JPEG Compression (quality factor: 80), perceptual transparency and poor correlation between contrast adjustment (20) and false positive problem original and extracted watermark. checking. Transform domain methods insert watermark in transformed coefficients of cover mage. They have M. OPTIMIZATION BASED WATERMARKING better watermark hiding capacity and better TECHNIQUES: robustness compared to spatial domain watermarking It is challenging issue to achieve robustness and methods. imperceptibility i.e. fidelity under high payload scenario DWT has multi-resolution property and it is most maintaining security of underlying watermarking popular transform preferred for image watermarking. technique. Some researchers proposed optimization based As per international standard organization (ISO) solutions. DCT-Singular Value Decomposition (SVD) based norms, JPEG2000image compression standard has genetic algorithm(GA) technique by Chih-Chin Lai et replaced DCT by DWT. Hence majority of researchers al.[45], wavelet based GA method by K.Ramanjaneyulu et are focusing on DWT for implementation of al.[46], quantization with DWT-SVD non-dominated watermarking frameworks. Sorting Genetic Algorithm-II proposed by Jiann-Shu Lee et In spread Spectrum communication, a narrow band al.[47] are example GA based techniques proposed used signal is transmitted over larger bandwidth such that for optimization of robustness and fidelity. Particle swarm signal energy present in any frequency is undetectable. optimization effectively explores solution space for Spreading the watermark through spread spectrum of optimal feature subset as per criteria specified as per image ensures large measure of security. But spread requirement of the application. The particle swarm spectrum based watermarking methods have low optimization with feature based robust image watermark information hiding capacity. watermarking using DWT-SVD is proposed by Chih-Chin Many researchers working in watermarking field have Lai et al.[48] . SulagnaLaha et al.[49] proposed robust tried to prove that watermarking techniques using 62 | P a g e
NOVATEUR PUBLICATIONS International Journal of Research Publications in Engineering and Technology [IJRPET] ISSN: 2454-7875 VOLUME 3, ISSUE 8, Aug. -2017 composition of two or three transforms give better Transform”, IEEE Transactions on Signal Processing, performance than single transform. Vol. 58, No. 11, pp. 5901-5909, Nov. 2010. The most of the existing image watermarking methods 6) Wen-Nung Lie and Guo-Shiang Lin,” A Feature-Based have failed to achieve imperceptibility and robustness Classification Technique for Blind Image Steganalysis”, simultaneously. These quality parameters conflict each IEEE Transactions On Multimedia, Vol. 7, No. other under high watermark embedding capacity. 6,pp.1007-1019, Dec. 2005. The GA based optimization techniques are presented 7) Fabrizio Guerrini, Masahiro Okuda, Nicola Adami, and by some researchers to optimize perceptual Riccardo Leonardi,” High Dynamic Range Image transparency and robustness by embedding high Watermarking Robust Against Tone-Mapping payload. But slow execution speed is limitation of GA Operators”, IEEE Transactions On Information based methods as it searches optimizes solution in Forensics and Security, Vol. 6, No. 2,pp.283-295, Jun. large space. 2011. The watermark scrambling methods are used to 8) Fan Zhang, Wenyu Liu, Weisi Lin, and King Ngi Ngan, convert image into unrecognizable patterns so that ”Spread Spectrum Image Watermarking Based on extracted watermark cannot be recognized directly. Perceptual Quality Metric”, IEEE Transactions on Image Hence the scrambling methods are effectively used by Processing, Vol. 20, No. 11, pp. 3207-3218, Nov. 2011. many researchers for security provision. 9) Minoru Kuribayashi,” Simplified MAP Detector for Binary Fingerprinting Code Embedded by Spread ACKNOWLEDGMENT: Spectrum Watermarking Scheme”, IEEE Transactions The author expresses deep sense of gratitude and on Information Forensics and Security, Vol. 9, No. 4, hearty thanks to her Ph.D supervisor Dr. Suresh N. Mali, pp. 610-623, Apr. 2014. Principal, Sinhgad Institute of Technology and Science 10) Mohsen Zareian, Hamid Reza Tohidypour, “Robust (SITS), Narhe, Pune, MS, India for his valuable guidance, quantization index modulation-based approach for motivation and support for this research work. The author image watermarking”, IET Image Processing, Vol. 7, Iss. would also like to thank to Dr. M.A. Venkatesh, Principal 5, pp. 432–441, Apr. 2013. Amrutvahini College of Engineering, Sangamner, 11) Xiangui Kang, Jiwu Huang, Wenjun Zeng, ”Improving Ahmednagar, Maharashtra, India for his constant support.. Robustness of Quantization-Based Image Watermarking via Adaptive Receiver”, IEEE Transactions on REFERENCES: Multimedia, Vol. 10, No. 6, pp.953-959,Oct. 2008. 1) Tanushyam Chattopadhyay, Brojeshwar Bhowmick, 12) Soo-Chang Pei and Jian-Jiun Ding, “Reversible Integer and Aniruddha Sinha,” Applications of Image Color Transform”, IEEE Transactions on Image Processing in Industries”, Computer Society of India Processing, Vol. 16, No. 6, pp.1686-1691, Jun. 2007. Communications (CSIC), Vol: 36, Issue 4, pp.8-11, Jul. 13) Chun-Hsien Chou and Kuo-Cheng Liu, “A Perceptually 2012. Tuned Watermarking Scheme for Color Images”, IEEE 2) Mohammed, Ghassan N., Yasin, Azman ; Zeki, Akram Transactions on Image Processing, Vol. 19, No. 11, pp. M, ”Robust image watermarking based on Dual 2966 - 2982, Nov. 2010. Intermediate Significant Bit (DISB)”, IEEE 6th 14) Paulo Vinicius Koerich Borges, Joceli Mayerand Ebroul International Conference on Computer Science and Izquierdo, “Robust and Transparent Color Modulation Information Technology (CSIT) , pp:18–22, 26-27 Mar. for Text Data Hiding”, IEEE Transactions on 2014. Multimedia, Vol. 10, No. 8,pp. 1479, Dec. 2008. 3) Tsung-Yuan Liu, and Wen-Hsiang Tsai, “Generic 15) Shang-Lin Hsieh, Jh-Jie Jian, I-Ju Tsai, and Bin-Yuan Lossless Visible Watermarking-A New Approach”, IEEE Huang, “A Color Image Watermarking Scheme Based on Transactions on Image Processing, Vol. 19, No. 5, pp. Secret Sharing and Wavelet Transform”, IEEE, pp. 1224-1235, May 2010. 2143-2148,2007. 4) Md. Iqbal H. Sarker, M. I. Khan, “An Improved Blind 16) Guangmin Sun,Yao Yu,” DWT Based Watermarking Watermarking Method in Frequency Domain for Image Algorithm of Color Images”, Second IEEE Conference Authentication”, IEEE International Conference on on Industrial Electronics and Applications, pp.1823Informatics, Electronics & Vision (ICIEV) , pp.1-5, 171826, 2007. 18 May 2013. 17) Hao-Tang Chan, Wen-Jyi Hwang, and Chau-Jern Cheng, 5) Jiasong Wu, Huazhong Shu, Lu Wang, and Lotfi “Digital Hologram Authentication Using a HadamardSenhadji, “Fast Algorithms for the Computation of Based Reversible Fragile Watermarking Algorithm”, Sliding Sequency-Ordered Complex Hadamard Journal of Display Technology, Vol. 11, No. 2, pp. 193203, Feb. 2015. 63 | P a g e
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