IT14 Watermarking Techniques in Medical images

Transcription

IT14 Watermarking Techniques in Medical images
Watermarking Techniques in Medical images
- A Survey
Dr. S. Karthikeyan
Dr. Alex Mathew
College of Applied Sciences, Sohar
Sultanate of Oman
karthikeyan.soh@cas.edu.om
College of Applied Sciences, Sohar
Sultanate of Oman
dr.alex.soh@cas.edu.om
Mrs. Sathya Degala
College of Applied Sciences, Sohar
Sultanate of Oman
degala_sathya.soh@cas.edu.om
Abstract—Medical imaging modalities generate colossal
dimensions of medical images every day. Medical images are
often transmitted over insecure channel. Hence protection of
medical image is very crucial for accurate diagnosis and patient
confidentiality. Furthermore there is a rise of various diseases,
for which few diagnoses are insufficient; therefore to achieve a
correct diagnostic, there is need to exchange the data over
internet. The key problem of exchanging the data over internet is
to maintain their authenticity, integrity and confidentiality.
Therefore, we need a system for effective transmission and access
of medical images keeping its authenticity, integrity and
confidentiality. In this paper, we discuss various types of water
marking, features, requirements, techniques and its pros and
cons were analysed.
Keywords—Medical Images, Watermarking, DCT, Least
Significant Bit Modification (LSB), Discrete Fourier Transform
(DFT), Discrete Cosine Transform (DCT), Discrete Wavelet
transforms (DWT), Curvelet Transform.
I. INTRODUCTION
Medical Imaging is an essential part of medical care
in the world. It means examining patients with DICOM
images to help doctors and other health-care professionals
make the correct clinical diagnosis and use this critical
information to decide on the appropriate treatment. Medical
Images are produced by varying imaging modalities such as
Computer Tomography (CT), Magnetic Resonance Imaging
(MRI), Ultra Sound (US). Picture archiving and
communication system (PACS) is a medical imaging
technology which provides economical storage of and
convenient access to images from multiple modalities. PACS
are installed in medical center to manage the medical image
information.
Medical images must need well-built security in view
of its importance in clinical diagnosis and treatment. Now-adays exchange of medical images between medical centers
located in different geographical location is very common. In
this case, to achieve a correct diagnostic, there is need to
exchange the data over Internet. The key problem of
exchanging the data over internet is to maintain their
authenticity, integrity and confidentiality. Therefore, we need
a system for effective transmission and access of medical
images keeping its authenticity, integrity and confidentiality
[11].
Digital watermarking is a security technique which is capable
to handle all security issues. It is defined as a pattern in which
bits are inserted into audio, digital image, text file or video
which detects the copyright information of the file. In the
digital watermarking the secret information are implanted into
the original data for protecting the ownership rights of the
multimedia data. This paper discusses various features of the
watermarking, water marking requirements, suitable
Watermarking techniques in medical images and its pros and
cons were analysed and presented.
The rest of this paper is organized as follows. Section
2 describes Digital Watermarking Feature, Classifications,
Types, Techniques and its pros and cons were presented.
Finally, some conclusions are drawn in Section 3.
II. DIGITAL WATER MARKING
In the year 1988, the digital watermarking is used by
Komatsu and Tominaga. Watermark is defined as a pattern in
which bits or digital signals are inserted into audio, digital
image, text file or video which detects the copyright
information of the file. These watermarks are the faintly
visible imprints in the stationary and the digital watermarks
protect fully the intellectual property available in the digital
format. The main requirements of digital watermarking are
invisibility, robustness and data hiding capacity [5].
A. Need for Watermarking in Medical Images
Digital Watermarking is very important in Medical image
due to
(i)
Medical image transmission cannot be accessed
by unauthorized parties (confidentiality)
(ii)
Received images are not modified during
transmission (integrity),
(iii)
Images are from correct sources to the claimed
receivers (authentication). Continuously updated
Digital Imaging and Communication in medicine
(DICOM) standards provide guidelines to ensure
authentication, integrity and confidentiality of
medical images [5].
B. Digital Watermarking Classifications
Some of the important types of watermarking based on
different watermarks [12] [4] [6] are given below:
Visible watermarks: Visible watermarks are an extension of
the concept of logos. Such watermarks are applicable to
images only. These logos are inlaid into the image but they are
transparent. Such watermarks cannot be removed by cropping
the center part of the image. Further, such watermarks are
protected against such as statistical analysis. Watermark
Embedding
Key
Watermark
Recovery
Watermark
Watermarked image Watermark Key Image Watermarked
Image. The drawbacks of visible watermarks are degrading the
quality of image and detection by visual means only. Thus, it
is not possible to detect them by dedicated programs or
devices. Such watermarks have applications in maps, graphics
and software user interface.
Invisible watermark: invisible watermark is hidden in the
content. It can be detected by an authorized agency only. Such
watermarks are used for content and /or author authentication
and for detecting unauthorized copier.
Public watermark: Such a watermark can be read or retrieved
by anyone using the specialized algorithm. In this sense,
public watermarks are not secure. However, public
watermarks are useful for carrying IPR information. They are
good alternatives to labels.
Fragile watermark: Fragile watermark are also known as
tamper-proof watermarks. Such watermark are destroyed by
data manipulation or in other words it is a watermarks
designed to be destroyed by any form of copying or encoding
other than a bit-for-bit digital copy. Absence of the watermark
indicates that a copy has been made.
Private watermark: Private watermarks are also known as
secure watermarks. To read or retrieve such a watermark, it is
necessary to have the secret key.
C. Features of Digital Watermarking
Various features of watermarking are as follows.
Imperceptibility: Watermark cannot be seen by human eye or
not be heard by human ear, only be detected through special
processing. To preserve the quality of the marked document,
the watermark should not noticeably distort the original
document. Ideally, the original and marked documents should
be perceptually identical.
Robustness: Robustness refers to that the watermark
embedded in data has the ability of surviving after a variety of
processing operations and attacks. Robustness means that it
must be difficult to defeat a watermark without degrading the
marked document severely-so severely that the document is no
longer useful or has no value.
Security:
A watermark system is said to be secure, if the hacker cannot
remove the watermark without having full knowledge of
embedding algorithm, detector and composition of watermark.
A watermark should only be accessible by authorized parties.
This requirement is regarded as a security and the watermark
is usually achieved by the use of cryptographic keys.
Watermark information owns the unique correct sign to
identify, only the authorized users can legally detect, extract
and even modify the watermark, and thus be able to achieve
the purpose of copyright protection [13].
No reference to original document: For some applications, it
is necessary to recover the watermark without requiring the
original, unmarked document (which would otherwise be
stored in a secure archive) [8].
Multiple watermarks: It may also be desirable to embed
multiple watermarks in a document. For example, an image
might be marked with a unique watermark each time it is
downloaded [8].
Verifiability: Watermark should be able to provide full and
reliable evidence for the ownership of copyright-protected
information products. It can be used to determine whether the
object is to be protected and monitor the spread of the data
being protected, identify the authenticity, and control illegal
copying [13].
Computational cost: In order to reduce computational cost, a
watermarking method should be less complex. Watermarking
methods with high complex algorithms will require more
software as well as hardware resources and thus incur more
computational cost. Computational simplicity usually
preferred in resource-limited environments like mobile
devices [13].
D. Types of Digital Watermarking
Watermarking algorithms are divided into two categories.
Spatial-domain techniques work with the pixel values directly.
Spatial domain techniques are simple and fast. Frequencydomain techniques employ various transforms, either local or
global. Transform domain techniques are more robust to
attacks several widely recognized techniques are described
subsequently.
Spatial Domain Watermarking Methods
In this technique, the watermark is inserted in the cover image
changing pixels or image characteristics [2].
Least Significant Bit Modification (LSB): LSB is the most
familiar technique in hiding a watermark in an image it
depends on modifications done to the least significant bits of
certain pixels in the image. LSB is classified as a spatial
domain technique in which the watermark size is very smaller
than the cover object, the watermark can be embedded
repeatedly in certain places in the cover object, these marks
maybe lost during the opponent attacks but part of the marks
will resist the attacks. LSB use some kind of cryptography on
the watermark message before the embedding, process [14].
Merits:
Least Significant Bit algorithm is strong and less
perceptible. Watermark is embedded into an image by
replacing least significant bit to hide the information.
Demerits:
It suffers from many drawbacks such as highly
sensitive to noise and easily destroyed.
It can survive simple operation such as cropping, any
addition of noise. However lossy compression is going to
defeat the watermark. An even better attack is to set all the
LSB bits to ‘1’ fully defeating the watermark at the cost of
negligible perceptual impact on the cover object. Furthermore,
once the algorithm was discovered, it would be very easy for
an intermediate party to alter the watermark [1].
Frequency Domain Watermarking Method
Compared to spatial-domain methods, frequency-domain
methods are more widely applied. The produce of high quality
watermarked image is by first transforming the original image
into the frequency domain by the use of Discrete Fourier
Transform (DFT), Discrete Cosine Transform (DCT), Discrete
Wavelet transforms (DWT), Curvelet Transform method.
With this technique, the marks are not added to the intensities
of the image but to the values of its transform coefficients.
Then inverse transforming the marked coefficients forms the
watermarked image. The use of frequency based transforms
allows the direct understanding of the content of the image;
therefore, characteristics of the human visual system (HVS)
can be taken into account more easily when it is time to decide
the intensity and position of the watermarks to be applied to a
given image.
Some of its main algorithms are discussed below:
Discrete Cosine Transform (DCT): DCT like a Fourier
Transform, it represents data in terms of frequency space
rather than an amplitude space. This is useful because that
corresponds more to the way humans perceive light, so that
the part that are not perceived can be identified and thrown
away. DCT based watermarking techniques are robust
compared to spatial domain techniques. Such algorithms are
robust against simple image processing operations like low
pass filtering, brightness and contrast adjustment, blurring etc.
However, they are difficult to implement and are
computationally more expensive. At the same time they are
weak against geometric attacks like rotation, scaling, cropping
etc. DCT domain watermarking can be classified into Global
DCT watermarking and Block based DCT watermarking [3].
Embedding in the perceptually significant portion of the image
has its own advantages because most compression schemes
remove the perceptually insignificant portion of the image.
Discrete Wavelet Transforms (DWT): Wavelet Transform is
a modern technique frequently used in digital image
processing, compression, watermarking etc. The transforms
are based on small waves, called wavelet, of varying
frequency and limited duration. The wavelet transform
decomposes the image into three spatial directions, i.e.
horizontal, vertical and diagonal. Hence wavelets reflect the
anisotropic properties of HVS more precisely. Magnitude of
DWT coefficients is larger in the lowest bands (LL) at each
level of decomposition and is smaller for other bands (HH,
LH, and HL). The Discrete Wavelet Transform (DWT) is
currently used in a wide variety of signal processing
applications, such as in audio and video compression, removal
of noise in audio, and the simulation of wireless antenna
distribution. Wavelets have their energy concentrated in time
and are well suited for the analysis of transient, time-varying
signals. Since most of the real life signals encountered are
time varying in nature, the Wavelet Transform suits many
applications very well [16]. One of the main challenges of the
watermarking problem is to achieve a better tradeoff between
robustness and perceptivity. Robustness can be achieved by
increasing the strength of the embedded watermark, but the
visible distortion would be increased as well [16]. However,
DWT is much preferred because it provides both a
simultaneous spatial localization and a frequency spread of the
watermark within the host image [5]. The basic idea of
discrete wavelet transform in image process is to multidifferentiated decompose the image into sub-image of
different spatial domain and independent frequencies [15].
Advantages of DWT over DCT
1) Wavelet transform understands the HVS more closely than
the DCT.
]2) Wavelet coded image is a multi-resolution description of
image. Hence an image can be shown at different levels of
resolution and can be sequentially processed from low
resolution to high resolution.
3) Visual artifacts introduced by wavelet coded images are
less evident compared to DCT because wavelet transform
doesn't decompose the image into blocks for processing. At
high compression ratios blocking artifacts are noticeable in
DCI; however, in wavelet coded images it is much clearer.
4) DFT and DCI are full frame transform, and hence any
change in the transform coefficients affects the entire image
except if DCT is implemented using a block based approach.
However DWT has spatial frequency locality, which means if
signal is embedded it will affect the image locally [9]. Hence a
wavelet transform provides both frequency and spatial
description for an image.
Disadvantages of DWT over DCT
1) Computational complexity of DWT is more compared to
DCT' [12]. As Feig (1990) pointed out it only takes 54
multiplications to compute DCT for a block of 8x8, unlike
wavelet calculation depends upon the length of the filter used,
which is at least 1 multiplication per coefficient [3].
Discrete Fourier Transform (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
the image but not the magnitude representation, or circular
shifts in the spatial domain 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
to recover from geometric distortions, whereas the spatial
domain, DCT and the DWT are not RST invariant and hence it
is difficult to overcome from geometric distortions [16].
Disadvantage of DFT over DWT and DCT:
The main disadvantage of the DFT is that the output of the
DFT is always in complex value and it requires more
frequency rate. Its computational efficiency is very poor. So,
the DFT not used because of these disadvantages.
Curvelet Transform
The Curvelet transform has provided stable, highly effective
expression for image with the smooth irregularity curve. The
Curvelet transform has anisotropy and the very strong
directivity. It is more suitable for image processing than the
wavelet and can represent smooth and edge of image with
sparsity [7].
TABLE 1 : COMPARISON OF WATERMARKING TECHNIQUES
Methods
LSB
DCT
DWT
DFT
Merits
1. Easy to implement
and understand
2. Low degradation of
image quality
3. High perceptual
transparency.
1. The watermark is
embedded into the
coefficients of
the
middle frequency, so
the visibility of image
will not get affected
and the watermark will
not be removed by any
kind of attack.
1.
Allows
good
localization both in
time
and
spatial
frequency domain.
2.Higher compression
ratio which is relevant
to human perception.
DFT is rotation, scaling
and translation (RST)
invariant. Hence it can
be used to recover from
geometric distortions
Demerits
1. It lacks basic
robustness
2. Vulnerable to noise
3. Vulnerable to
cropping, scaling.
1. Block wise DCT
destroys the invariance
properties of the system.
2. Certain higher
frequency components
tend to be suppressed
during the quantization
step.
Curvelet transform
Good invisibility and
robustness
Complexity is more and
large
amount
of
redundancy
E. Issues in medical image watermarking
Medical image watermarking is a special type of
watermarking technique where the watermarked medical
images should not differ perceptually from the original
images, because the diagnosis must not be affected due to the
presence of watermark. The biggest challenge in medical
image watermarking is that, the image may not undergo any
major degradation that will affect the quality of images with
visible alteration to their original form [15].
The second issue is either the watermarks are reversible or
permanent [7].
The third issue is if we decide to have watermarks for content
authentication, compression should be distinguished from
other manipulations.
Conclusion
Watermarking has its place in security. It is not intended to
replace cryptography or steganography but supplement them.
Watermarking technologies are aimed at Robust proof of
copyright ownership. The most important use of watermarking
techniques will probably be lying in hiding the data without
visible to the viewer.
In this survey most important aspect of medical image
watermarking such as classification, features, techniques are
studied. Medical image watermarking technique still has not
matured. Though several techniques have been proposed still
the research on Medical Image Watermarking has to continue
to solve many watermarking issues. Digital watermarking
seems to be the only potential encryption technology to
provide protection even after data is decrypted. Future work
would be directed to develop a hybrid watermarking scheme
which will be robust to a larger variety of attacks, a multiband watermark embedding technique (MBE) that and
preserves high diagnostic quality, instead of DWT, DCT,
DFT, Curvelet transform use of Complex Transforms (CT)
will make the system more robust and secure, digital
signatures will be used for complete authentication.
REFERENCES
[1]
Darshana Mistry,(2010).Comparison of Digital Water Marking
methods, International Journal on Computer Science and
Engineering, 2(9):2905-2909.
1. Cost of computing
may be higher.
2.Longer compression
time.
3. Noise/blur near edges
of images or video
frames.
[2]
El-Gayyar.M. and J. von zur Gathen, (2006). Watermarking
techniques spatial domain, University of Bonn Germany, Tech.
Report.
[3]
Ephraim Feig and Shmuel winograd, (1992). Fast Algorithms for
the Discrete Cosine Transform, IEEE Transaction on Signal
Processing, 40(9): 2174: 2193.
1.Complex
implementation
2. Cost of computing
may be higher.
[4]
Hartung, F. and M. Kutter, (1999). Multimedia watermarking
techniques, Proceedings of the IEEE, special issue on protection of
multimedia content, 87(7):1079-1107.
[5]
HEMA, “DICOM: Digital imaging and communication in
medicine,” [Online], Available: http://medical.nema.org/
[6]
http://www.networkmagazineindia.com/200108/security1.htm.
[7]
Jasni Zain and Malcolm Clarke, (2005). Security In Telemedicine:
Issues In Watermarking Medical Images, In: Proceedings of the
IEEE International Conference: Sciences of Electronic,
Technologies of Information and Telecommunications.
[8]
Jonathan K. Su, Frank Hartung and Bernd Girod, (1999). Digital
Watermarking of Text, Image, and Video Documents.
[9]
Lee, C. and H. Lee, (2005). Geometric attack resistant
watermarking in wavelet transform domain, Optics Express,
13(4):1307-1321.
[10]
Manpreet Kaur, Sonika Jindal & Sunny Behal, (2012). A Study of
Digital Image Watermarking. International Journal of Research in
Engineering & Applied Sciences, 2(2):126-136.
[11]
Mohamed Ali Hajjaji, Abdellatif Mtibaa and El-bey Bourennane,
(2011). A Watermarking of Medical Image: Method Based
"LSB"”, Journal of Emerging Trends in Computing and
Information Sciences, 2(12):714-721.
[12]
Petitcolas, F. A. P., R.J. Anderson, R. J. and M. G. Kuhn,
(1999).Information hiding - A survey, Proceedings of the IEEE,
special issue on protection of multimedia content, 87(7):10621078.
[13]
Prabhishek Singh and R S Chadha, (2013). A Survey of Digital
Watermarking Techniques, Applications and Attacks, International
Journal of Engineering and Innovative Technology (IJEIT),
2(9):165-175.
[14]
Riaz, S., M. Y. Javel, and M. A. Anjum, (2008). Invisible
watermarking scheme in spatial and frequency domains,
International Conference on Emerging Technologies.
[15]
Tanmay Bhattacharya, Sirshendu Hore, S. R. Bhadra Chaudhuri,
(2014). A Semi-Fragile Blind Digital Watermarking Technique for
Medical Image File Authentication using Stationary Wavelet
Transformation,
International
Journal
of
Computer
Applications,104(11): 8-13.
[16]
Vidyasagar M. Potdar, Song Han and Elizabeth Chang, (2005). A
Survey of Digital Image Watermarking Techniques, In:
Proceedings of the 3rd IEEE International Conference on Industrial
Informatics (INDIN), 709-716.
[17]
Zhu, W., Z.Xiong, and Y.-Q. Zhang, (1999). Multiresolution
Watermarking for Images and Video, IEEE Transaction on circuit
and System for Video Technology, 9(4):545-550.