=Paper=
{{Paper
|id=Vol-2889/PAPER_14
|storemode=property
|title=A Comprehensive Review on Digital Image Watermarking
|pdfUrl=https://ceur-ws.org/Vol-2889/PAPER_14.pdf
|volume=Vol-2889
|authors=Shweta Wadhera,Deepa Kamra,Ankit Rajpal,Aruna Jain,Vishal Jain
}}
==A Comprehensive Review on Digital Image Watermarking==
https://ceur-ws.org/Vol-2889/PAPER_14.pdf
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.
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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.
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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
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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].
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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].
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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
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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]
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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. Through the paper, we analyze various watermarking methods in digital images
used in the recent past.
7. References
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