A Comprehensive Review on Digital Image Watermarking Shweta Wadheraa,b*, Deepa Kamrac, Ankit Rajpal d, Aruna Jaine and Vishal Jainf a Department of Computer Science, Deen Dayal Upadhyaya College, University of Delhi, New Delhi, India b Research Scholar, Sharda University, Greater Noida, India c Department of Management Studies, Deen Dayal Upadhyaya College, University of Delhi, New Delhi, India d Department of Computer Science, University of Delhi, New Delhi, India e Department of Computer Science, Bharati College, University of Delhi, New Delhi, India f School of Engineering and Technology, Department of Computer Science and Engineering, Sharda University Greater Noida, India Abstract The advent of the Internet led to the easy availability of digital data like images, audio, and video. Easy access to multimedia gives rise to the issues such as content authentication, security, copyright protection, and ownership identification. Here, we discuss the concept of digital image watermarking with a focus on the technique used in image watermark embedding and extraction of the watermark. The detailed classification along with the basic characteristics, namely visual imperceptibility, robustness, capacity, security of digital watermarking is also presented in this work. Further, we have also discussed the recent application areas of digital watermarking such as healthcare, remote education, electronic voting systems, and the military. The robustness is evaluated by examining the effect of image processing attacks on the signed content and the watermark recoverability. The authors believe that the comprehensive survey presented in this paper will help the new researchers to gather knowledge in this domain. Further, the comparative analysis can enkindle ideas to improve upon the already mentioned techniques. Keywords 1 Digital Watermarking, Digital images, review, visual imperceptibility, robustness, copyright protection 1. Introduction In the present era, the secret to the success of an organization is all about the information it can gather. Also, of concern is how effectively it can stop others from accessing the information generated through its operations and processes. The popularity and availability of the Internet, easy access to digital storage devices, have made the creation, replication, and distribution of digital media hassle-free. This has led to the strong need of developing methods for preventing copyright breaches [1, 2]. The technique of digital watermarking is being applied widely to the situations where an organization wants to deter the data from spilling into the public domain. It is extremely crucial in cases where the company is in direct fiduciary relationship with its customers and must protect their information as well [1]. WCNC-2021: Workshop on Computer Networks & Communications, May 01, 2021, Chennai, India. EMAIL: shweta.du@gmail.com (Shweta Wadhera) ORCID: 0000-0002-3123-9976 (Shweta Wadhera) © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (CEUR-WS.org) 126 Digital Watermarking is a method to provide protection from any tampering or alteration [3, 4, 5]. It provides security and authentication to digital content. The digital watermarking process involves the insertion of signal, information into the original media content. The inserted information is then uncovered and extracted to report the actual owner of the digital media. Watermarking involves embedding data called watermark or digital signature or label into the digital media. This watermark can be extracted for revealing the authenticity of the media object [6]. As an example of a watermark, we can imagine a visible “seal” over an image. A digital watermarking algorithm has three basic parts: - 1. Watermark 2. The Encoding algorithm 3. The decoding algorithm [1, 7, 8]. Figure 1: The block diagram of Digital Watermarking Concept This technique may be used for copyright safeguarding and embedding fingerprints, placing authentication for data integrity checks, and confidential communication. Another important application of watermarking techniques includes tracing illegal users with an objective that the owner can approach the regulatory authorities. It can be useful for ensuring that data pertaining to people who buy and sell digital media, kept in record for each transaction. Further track of this data can be kept for controlling copyright breaches. In fact, strict measures must be implemented for this unlawful distribution of digital content. The paper is consolidated as follows: section 2 presents the classification of digital watermarking based on various characteristics. Section 3 describes the prominent features of digital watermarking. Section 4 covers the recent areas of application for watermarking. Section 5 presents the various types of attacks. In section 6 we analyze the highlights and results of related work by various authors and section 7 presents the conclusions and future scope in the direction of image watermarking. 2. Classification of Digital Watermarking The section describes the classification of digital watermarking based on various criteria such as robustness, perceptibility, domain, and detection process, multimedia. Further we also briefly present the different popular watermarking techniques. 127 2.1. Based on Characteristics/Robustness Robust: Robust watermarking is preferred when copyright information is required to be inserted. Robustness is indicated if the embedded watermark even after some attack is not damaged. It can withstand several attacks. It is seen that for copyright protection, a robust watermark is advantageous. Fragile: One can easily find out from the status of the watermark if the data has been altered. For integrity protection, this watermark is preferred. Semi-fragile: Some extent of change is tolerated by a semi-fragile watermark [2, 3, 6]. 2.2. Based on Perceptibility Perceptible: A watermark that is visible is known as perceptible. Imperceptible: Incase the watermark is invisible then it is known as imperceptible watermark. In this, information which is embedded into the image is not visible. In such cases one can prove the ownership of your image with the help of imperceptible watermark [2, 26]. 2.3. Based on Domain Frequency domain: First, the transforming of the image to the frequency domain is carried out. In this type of watermarking different transformation techniques are applied such as DCT, DFT, and DWT [27]. Spatial Domain: Watermarking in this domain moderately changes the value of pixels, of arbitrarily selected portions of images; the watermark is inserted in the host image. No conversion or transformation is applied in the spatial domain. LSB, Patchwork method, SSM Modulation are some of the popular spatial domain-based techniques [2, 3]. Generally, the watermarking carried out in the frequency domain is more robust as compared to the one carried out in the spatial domain. 2.3.1. Spatial Domain Least Significant bit (LSB) method In this method, the watermark is inserted in the least significant bit (LSB of image pixels. Ideally, either of two ways is used for embedding. In one approach, the LSB of an image is substituted with a pseudo-noise (PN) sequence, while another approach adds this PN sequence to the LSB. LSB technique provides ease of use but compromises on the robustness parameter against attacks. Patchwork Method Patchwork method randomly picks n pairs of image points (x, y). The data in the x region is lightened and data in the y region is darkened. However, this technique can withstand a series of attacks, but it lacks in terms of capacity. 128 Figure 2: Classification of Digital watermarking 2.3.1. Frequency Domain Discrete cosine transforms (DCT) This method employs a technique of subdividing an image signal into non-overlapping blocks of 8 × 8 size. Further, block-wise DCT is performed, and thereafter the choice of coefficients to be watermarked is carried out. Finally, an inverse DCT is applied on each 8 × 8 block to obtain the signed image. Discrete wavelets transform (DWT) In this method, the image is subjected to a sequence of low-pass and high-pass filters. An image is decomposed into four equal sub-bands where each sub-band comprises low frequency (LL), horizontal features (LH), vertical features (HL), and diagonal features (HH). It is a preferred algorithm as it provides a robust and secure watermarking method [2, 3, 27]. Figure 3: Three level decomposition in 2D DWT 129 2.4. Based on Detection process  Blind: Those watermarking processes fall in this category wherein the removal of the embedded information requires only the watermarked image. Its applications can be copyright protection, e- voting, etc. [9].  Non-Blind: In this type of watermarking, the process copies along with the text data, the host image, and the inserted information for the retrieval of the watermark. Its application is seen in copyright protection [9]. 2.5. Based on Multimedia  Text Watermarking: It consists of components like words, punctuations, sentences, etc. Transformation is done on one of these components and is embedded as a watermark [3].  Image Watermarking: Large-size images are there which has to be watermarked. In the case of images, we require robust watermarks, which should be imperceptible [3].  Video watermarking: In this case, it is difficult to get imperceptible watermark.  Graphic Watermarking: In 2D or 3D digital graphics, a watermark is embedded. It provides copyright protection. 3. Basic Characteristics of Digital Watermarking Mentioned here are various features of Digital Watermarking.  Robustness: The robustness feature indicates that the digital watermark can resist various processing operations and attacks. Then it is considered to be robust [14].  Imperceptibility: The imperceptibility feature indicates that a digital watermark should not be seen by the human eye. One should not be able to see the embedded watermark. It can only be identified by specialized procedures. The watermark should be such that the viewer should not be able to see it and the process of embedding a watermark should be such that the quality of the content is maintained [14].  Security: The security feature indicates that irrespective of targeted attacks, the inserted digital watermark cannot be removed. Watermark security describes that altering or removing a watermark without any deterioration to the host signal should be arduous. Watermarking security can be explained as a way to provide secrecy, ownership, and protection of data [2].  Capacity: The amount of information embedded in a watermarked image also known as data payload [3]. 130 Figure 4: Basic Characteristics  Verifiability: Through the watermark, we should be able to get a piece of evidence regarding the ownership of copyright-protected data. This helps in verifying the authenticity of any digital data and even the control of its unlawful copying [29]. 4. Recent Applications of Watermarking  Copyright protection: As we are aware that images can be easily circulated and are freely available over the internet. These images can be used commercially. So copyright protection of data is needed and for this Digital Watermarking is very useful. The inserted digital watermark will be used to identify the copyright owner [2, 9].  Fingerprint: Fingerprinting in digital watermarking can be put up as a method for embedding some distinctiveness. The fingerprint should be difficult to alter. The information inserted is related to the customer. It is through this fingerprinting that it is revealed about those authorized customers who are involved in the circulation of copyright data by breaching the agreement [2, 27]. Figure 5: Applications of Digital Watermarking  Copy control: Digital watermarking can prevent illegal duplication of digital data. Devices that do replication can detect these watermarks and report copying and thereby put a control on illegal copying [3, 26]. 131  Broadcast Monitoring: Over the years it has been seen that availability and accessibility to media content have increased exponentially. Also, the content is available through the internet. In such times, it has become important for content owners and copyright owners to know about the real distributor of content. Digital Watermarking has an important role here [3, 26].  Medical Application: Embedding of patient name in the MRI-scan, CT-scan or X-ray reports can be done using visible watermarking. The treatment of the patient depends on these medical reports. So to avoid mixing of reports the technique of visible watermarking can be used [9].  Electronic Voting System: The Internet has spread all over the country from big towns to small villages. Electronic voting helps to carry out elections, keeping the security aspect into consideration [9].  Remote Education: Lack of teachers poses a big problem in small villages. Smart Technology needs to be adopted for distance learning. In this case watermarking plays its role in the authentic transmission of study material over the internet [9, 27]. 5. Attacks on Watermarking A digital Watermarking scheme is always assessed by the fact that how robust it is over attacks. Attack on any watermark is used to harm the inserted watermark or enfeeble the watermark's discovery. Hampering the protection, which a watermark provides to digital content, is the objective of any attack. Watermarking attacks can be classified as follows – Geometry attack, Protocol attack, Cryptographic attack, and removal attack [10, 11, 12].  Geometry Attack: Such processing is done over the watermark image which alters the geometry of the image like rotation, cropping, etc. These can be further classified into – scaling, cropping, rotation, and translation [6].  Removal Attack: This attack aims at removing the inserted data from the digital image. If it is not able to, yet they try to destroy the embedded information [29]. Figure 6: Types of Attacks on Digital Watermarking 132  Protocol Attack: The attacks which come under this category, do not damage the embedded data. Two types of Protocol attacks are there: Invertible, Copy attack. So a watermark should be non- invertible and should not be copied. A watermark is invertible when the attacker removes his own watermark from the host data. The attacker then pretends to be the owner of the data. This shows that for copyright protection, watermarks should be non-invertible [13, 29].  Copy Attack: It is also a form of Protocol attack. In this also the watermark is not destroyed. Instead, the attacker estimates the watermark from host data. It is then copied to other data [13].  Cryptographic Attack: These types of attacks include those which break the security in watermarking techniques. With this, they can extract the inserted watermark data or can insert some delusive watermark. The Brute-force and Oracle attacks fall under this category [29]. In order to present an exhaustive survey on image watermarking, we created a repository of more than 50 papers on Mendeley and 35 papers were used to develop the background of digital watermarking and 19 papers were found relevant in the area of image watermarking. Table 1 summarizes the watermarking schemes proposed by various research groups in the past few years through the comparative analysis. Table 1: Comprehensive survey of recent image watermarking schemes Research Title Technique used Input Visual Robustness group Imperceptibility Abraham “An Spatial domain Cover image PSNR = NCC = Range and Paul imperceptible Simple Image Colored 47.6 dB [0.9917 – 1] [6] spatial domain Region Detector image of color image (SIRD): Estimation Size: SSIM = BER= Range watermarking of most suitable 512 x 512 x 3 0.9904 [0.7500-0] scheme” portion within the pixels block of an image. Attacks Watermark considered: Size: 64 x 64 pixels Salt and Pepper, Poisson, Speckle, average filtering, Gaussian LPF, Sharpening, JPEG Compression, Cropping, Resizing Liu et al. “Secure and Scrambling Cover image PSNR NCC Range [7] robust digital Watermark: RSA Colored Range = =[0.6053 - image Encryption Size: 512 x [38.68 -48.03] 0.9673] watermarking 512 pixels dB scheme using DWT + SVD Hybrid Attacks 133 logistic and RSA Watermark Considered: encryption” Different Size: 256 x embedding strength 256 pixels Mean is used. Filtering, Median Filtering, Gaussian Noise, Salt & Pepper Noise, Rotation, Crop, JPEG compression Vaidya DWT-CT-Schur-SVD Cover image Watermark1 NCC=1.0 and “A robust semi- Colored Mouli blind Discrete Wavelet PSNR range = [14] watermarking Transform (DWT): Two [27.63-36.16] Attacks for color images 1-level Watermarks dB Considered: based on decomposition of Size: Salt & Pepper, multiple Contour Let 64 x 64 pixels SSIM range = Gaussian decompositions Transform (CT): 2- [0.9709- Noise, ” level on LL subband 0.9989] to obtain 𝐷 . Schur Transform: Watermark2 𝐷 is decomposed as 𝐷 = PSNR Range 𝑄 . 𝑃 . [𝑄 ] =[22.38- 31.59] Singular Value dB Decomposition (SVD): Watermark is inserted in 𝑃 . Liu et al. “Digital image Cover image PSNR Attacks [15] watermarking Fractal encoding Size: Range=[41-45 ] Considered: method based and DCT method 1024 x 1024 dB white noise on DCT and are combined for pixels attack, fractal double encryption Gaussian filter encoding“ for embedding Watermark attack, JPEG purpose. Size: compression 256 x 256 attack. pixels Savakar “Robust Secret key: Select Cover Image PSNR = NCC= and Ghuli Invisible Digital the place of Plenoptic Range[51.68- Range[0.9139- [16] Image insertion of the Size: 64.54] dB 1.0] 134 Watermarking logo. 512 x 512 Using Hybrid pixels SSIM= Scheme” DCT + SVD Hybrid Range[0.9989- Attacks Watermark 1.0000 ] Considered : Binary Size: Gaussian 50 x 20 pixels Noise, Speckle noise, Salt and pepper noise, Poisson Noise, Rotation, JPEG Compression Moosaza “A new DCT- Image Cover image PSNR= NCC = deh and based robust watermarking Size: Range[39.95- Range Ekbatanif image scheme based on 512 x 512 40.73] [0.7871- ard [17] watermarking DCT pixels 0.9901] method using teaching- Teaching-Learning- Watermark learning-Based Based Optimization Size: Attacks optimization” (TLBO): Automatic 32 x 32 pixels considered : detection of embedding Salt & pepper parameters and noise, suitable position for Uniform inserting the noise, Poisson watermark. noise, Gaussian noise, Scaling, Rotation, Cropping, Sharpening, Motion Filter, Disk filter, Wiener, Median filter, Gaussian Filter, JPEG compression Su et al. “Improved Watermark bits are Cover image PSNR = NCC= [18] wavelet-based embedded in the Colored Range [37.6262- Range image spatial domain on Size: 38.0535] [0.8413- watermarking DC coefficients 512 x 512 1.0000] through SPIHT” using 2D-DFT. pixels SSIM= 135 Watermark Range[0.9231- Size: 0.9414] 32 x 32 pixels “Improved DWT + DCT + SVD Cover image PSNR= NCC= Kumar et wavelet-based Set Partitioning in Size: Range Range al. [19] image Hierarchical Tree 512 × 512 [25.31- 38.47] [0.9422- watermarking (SPIHT) and Arnold pixels 0.9990 ] through SPIHT” transform for SSIM= enhancing Watermark Range Attacks robustness. Size: [0.971311- Considered 256× 256 0.999954 ] pixels Salt & Pepper, Gaussian Noise, JPEG compression, cropping, Rotation, Scaling attacks, Sharpening Mask, Median Filter, Histogram Kahlesse “A robust blind LSB substitution Cover Image PSNR > 40 dB NCC= nane color image method is used. Colored Range[0.6437- Fares et watermarking Watermark is Size: 0.98265] al. [20] based on embedded within 512 x 512 Fourier the mid-band Pixels Attacks transform coefficients and considered domain” frequency components. Watermark Gaussian Size: noise, random Gaussian sequence of filter, 45,000 bits Histogram, JPEG, rescaling, Rotation, cropping, Gaussian noise, Image sharpening, Blurring, rotation, JPEG compression, salt & Pepper 136 noise, Median filter, cropping, Rotation Yuan et “New image Blind watermarking Cover Image Watermark1 NCC = al. [21] blind method: Colored Range [0.9997 watermarking Two dimensional Size: PSNR = – 1] method based DCT is performed 512 × 512 range[36.3189- on two- on selected blocks. Pixels 38.2472] Attacks dimensional Middle frequency SSIM= range considered : discrete cosine coefficients are Two Colored [0.9149 - transform” embedded. watermarks 0.9441] JPEG(40), Size: JPEG 2000, 32 × 32 Gaussian Pixels Watermark2 white Noise, salt & pepper PSNR = Noise, Butter Range worth low- [36.1885 – pass filtering, 38.4066 ] Median filtering, SSIM = cropping Range [0.9154 – 0.9724 ] Anand “An improved Medical image Cover image PSNR = NCC= and DWT-SVD watermarking in MRI image of Range [0.9724 - Singh domain DWT-SVD domain. Size: [32.6229 - 0.9873] [22] watermarking Hamming code is 512 x 512 34.0455] for medical put to text Pixels Attacks information watermark before considered : Security” embedding. Watermark SSIM= Chaotic-LZW and Size: Range Salt & Pepper hyper Chaotic -LZW 256 x 256 [0.9950 - noise, are used. Pixels 0.9955] Gaussian noise, Rotation, JPEG compression, Speckle noise, Cropping, Median filter, Histogram equalization Mishra et “Bi-directional DWT-BELM Cover image PSNR= NCC= al. [23] extreme approach JPEG Range[42.49- Range[0.95- learning DWT: 4-level compressed 42.67] dB 1.00] 137 machine for Bi-directional ELM image semi-blind (B-ELM): Variant of Size: SSIM= BER= watermarking of ELM is modeled 512 x 512 Range Range compressed with LL4 Pixels [0.9960 - [0.0938 - images” coefficients for 0.9969] 0.1074 ] Semi-blind Watermark recovery. Binary Attacks Size: considered : 32 x 32 Pixels Low pass Gaussian filter, Median filter, Gaussian noise, Salt & Pepper noise, Rotation, Scaling, Cropping Ambadek “Digital Image DWT and Cover Image PSNR= NCC= ar et al. Watermarking encryption-based Size: 54.96 dB 0.9749 [24] Through watermarking. 228 × 228 Encryption and Pixels Attacks DWT for Considered : Copyright Watermark Protection” Size: Noise, grayscale Geometric, image Compression 90 × 90 pixels Su et al. “An Spatial domain Cover Image PSNR = NCC = [30] Approximate watermarking using Size: Range[40.0691- Range[0.9912- Schur Schur 512 x 512 40.6450] dB 1.0] Decomposition- Decomposition Pixels based Spatial Maximum Domain Color eigenvalues are Watermark SSIM = Attacks Image approximated and Size: [0.9594- Considered : Watermarking used for embedding 32 x 32 0.9681] Rotation, JPEG Method” and blind Pixels (30), JPEG extraction. 2000, Salt & Peppers noise, Gaussian Noise, Median filtering, Butterworth lowpass filtering, 138 Sharpening, Blurring, Scaling, Cropping Rajpal et “Multiple 4-level DWT Cover Image PSNR = [42-43] BER <=0.0029 al. [31] scaling factors decomposition is Size: dB based Semi- used. 512 x 512 Attacks Blind LL4 coefficients are Pixels Considered : Watermarking embedded with JPEG of Grayscale multiple scaling Watermark Compression, Images using factors. Size: Rotation, OS-ELM OS-ELM is used for 32 x 32 Pixels Gaussian Neural semi-blind noise, Salt & Network” watermarking. Pepper Hosny et “Parallel Multi- Moments of the Cover Image PSNR= NCC= al. [32] Core CPU and polar complex Size: Range [40.597 – For colored GPU for Fast exponential Colour 53.64 ] dB images and transform obtained images and Range Robust Medical using Simplified grayscale [0.9100 – 1.0] Image exact kernels are medical Watermarking” used for the images For Grayscale restoration of 256 x 256 SSIM= images watermark. Pixels Range [0.933 – Range 0.980] [0.9358 – 1.0] Watermark Size: BER= 32 x 32 For colored Pixels images Range [0 – 0.0156] For Grayscale images Range [0 – 0.0176] Attacks Considered : Rotation at various angles, Scaling factor, Translation, Scaling + Rotation, 139 Scaling + JPEG compression, Rotation + JPEG compression, JPEG compression, Salt & Pepper Noise, Gaussian Noise, Gaussian filtering, Median filtering Taha et “Adaptive Image Integer-based lifting Cover Image PSNR= NCC= al. [33] Watermarking wavelet transform Size: Range [32.3236 Range Algorithm Based is used. 512 x 512 – 40.5670] dB [0.7798 – 1] on an Efficient Pixels Perceptual Mapping SSIM= Model” Watermark Range Size: [0.9522 – BER= Binary 0.9883] [0 – 0.1914] 32 x 32 Pixels Attacks Considered : JPEG compression, Salt & Pepper, Gaussian Noise, Sharpen, Median Filter, Average filter, Rotate, Scale Down, Crop Rajpal et “Fast Digital Generation of Cover Image PSNR = [39.70- NCC = [0.71- al. [34] Watermarking watermark Colored 45.72] 0.99] of sequence using DCT Size: Uncompressed using host image 256 x 256 Colored Images Pixels SSIM = [0.9965- Attacks using Informed 0.9991] Considered : Bidirectional watermarking using Extreme Extreme Learning Low pass 140 Learning Machine (ELM) and Watermark Filter, Machine” Bi-directional ELM Size: Gaussian (B-ELM) 1024 x 1024 Noise, Scaling, Pixels Crop, JPEG compression Alshoura “A New Chaotic IWT-SVD Hybrid is Cover image PSNR= NCC= et al. [35] Image used. Size : Range [46.85 – Range Watermarking Random key is 512 x 512 52.33] dB [0.99101- Scheme Based generated using Pixels 0.99513] on SVD and cover image and the IWT” watermark image. Attacks This key is utilized Watermark Considered : for embedding of Grayscale Cropping, watermark using image Cutting, chaotic multiple Size: Translating, scaling factors 256 x 256 Shifting, (CMSF). Pixels Rotating, Scaling, Median filter, Gamma Correction, Median filter, Wiener filter, Histogram equalization, Salt Peppers Noise, Speckle Noise, Gaussian Filter, JPEG Compression In Table 1, a study and evaluation of work done in digital watermarking techniques in past are enumerated. The spatial domain and frequency domain techniques are some popular techniques examined in the past. Also, it has been observed that the spatial domain digital watermarking technique is less robust and hence less preferred. The performance of the watermarked image is evaluated through robustness, imperceptibility, security, and capacity. Among these the most preferred criteria, were the visual imperceptibility of the watermarked image and the robustness of the watermarking. In fact, the future work holds scope by combining techniques and using them in hybrid form to not only enhances the robustness of the watermarked image, but it may also reduce the drawbacks of each method considered separately. 6. Conclusions This paper gives an overview of techniques of digital image watermarking along with the detailed classification and characteristics. The various application areas such as medical, remote education, military, electronic voting systems have been presented. It has been seen that data security has become a top priority due to the extensive transmission of digital data. So, for providing authorized data or 141 safeguarding important data, digital watermarking is used. The performance of the watermarked images is evaluated through robustness, imperceptibility, security, and capacity. These are analyzed using peak signal to noise ratio and bit-error ratio. It was observed that robustness was a preferred criterion. Invisible watermarking is carried out for content authentication and proof of ownership. Research groups have preferred frequency domain techniques and have tried to work on balancing between robustness and visual imperceptibility. 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