Alattar’s Method Based Reversible Watermarking Technique of EPR Within Heart Sound in Wireless Telemonitoring Das Poulami1, Munshi Riya2, Dey Nilanjan3 1
M.Tech Scholar, JIS College of Engineering, Kalyani, Nadia, West Bengal. Email:
[email protected] 2
B.Tech Student, JIS College of Engineering, Kalyani, Nadia, West Bengal. Email:
[email protected]
3
Assistant Professor, Dept. of IT, JIS College of Engineering, Kalyani, West Bengal Email:
[email protected]
ABSTRACT Exchange of information amongst various hospitals and diagnostic centres for mutual availability of diagnostic and therapeutic case studies is quite common. EPR (Electronic Patient Record) or Hospital Logo can be hidden within a bio medical signal for high security while transferring EPR/Logo through the internet. Exchanging data amongst hospitals or diagnostic centres requires high level of reliability and security. Signal integrity can be verified, authenticity and achieved control over the copy process can be proved by adding watermark in the original information in multimedia content. Heart sound or heart beat is basically a digital signal caused due to the flow of blood through it. In this present work a reversible watermarking method (Alattar’s method) is used for watermark insertion and extraction in a heart sound. It can be seen that in this approach the correlation value of the original watermark and the extracted watermark is quite high. In this approach the Signal-to-Noise ratio (SNR) between the original signal and the Recovered signal markedly improves which clams the robustness of the method.
Keywords Alattar’s Method, Reversible Watermarking, EPR, Heart Sound.
1. INTRODUCTION Nowadays it is a widespread practice to exchange medical information among different hospitals and diagnostic centers. To protect information like EPR (Electronic Patient Record) while transferring requires high security. Watermark can be used to hide EPR within the diagnostic results of a patient which is a 1-D signal such as Heart Sound, ECG, EEG, EMG, EOG signals. Insertion of watermarks in signals can cause distortion in signals, which is not acceptable as the signals convey information required to detect diseases. Embedding of watermark in the bio-signals causes compromise to the diagnostic value of the bio-signals. Achieving watermarking technique in bio-signals is a challenging task. In reversible watermarking technique bio-signals and the watermark information both can be recovered. Thus there is no scenario of compromising diagnosis value of the bio-signals and as well as the watermark information. Heart sound is basically a noise caused by the heart beats and the flow of blood through the heart. Usually heart produces the sound Lub & Dub, where Lub is the first sound S1 and S2 is the second sound Dub. The time between S1 and S2 is systole (Lub-------Dub) , caused by the flow of blood from the heart to the lungs and body, flow of blood across the Pulmonic and Aortic valves. This sound primarily occurs due to closing of the bicuspid and tricupsid valves. They close because of the contraction of the ventricle. The time between S2 and S1 is diastole (Dub--------Lub) , caused by closing by the flow of blood from the atria to the ventricles, flow of blood across the bicuspid and tricuspid valves.
S1 occurs at the onset of the ventricular contraction. It contains a series of low-frequency vibrations, and is usually the longest and loudest heart sound. S2 occurs at the end of the ventricular contraction. Its frequency is higher than S1, and its duration is shorter. S3 (ventricular gallop) is a low frequency sound, may be heared at the beginning of the diastole during the rapid filling of the ventricles. S4 (atrial gallop) may be heared in late diastole during atrial contraction. Other - opening snap, ejection sound may be heared at the time of valve diseases. Murmurs are high frequency noise like sounds which may be heared between the two major heart sounds systole and diastole. Anatomy of heart sounds can be obtained by the follwing : LUB-- DUB-------------LUB--DUB S1
S2
S3
S4 S1
S2
Watermarking is the process of embedding data into a 1-D or 2-D signal for security Purposes [11, 12, 13]. Reversible watermarking technique is a special type of watermarking scheme useful for restoring the original information from the watermarked information [2]. Retrieved watermark by using reversible watermarking can be used to determine the ownership by comparing it with the assigned watermark [9]. This feature is suitable for some important media such as medical and military media as these kinds of media does not allow any losses. Generally a good watermarking scheme must meet the following requirements: 1. Robustness, 2. Imperceptibility, 3. Readily embedding and retrieving. Similar to the conventional watermarking scheme reversible watermarking also have to be robust against the intentional and unintentional attacks, imperceptible to avoid the attention of attacks and value lost. In addition this scheme of watermarking satisfies the following two requirements: 1. Blind (Reversible watermarking can retrieve the original information from the watermarked information directly without using the original data), 2. Higher Embedding Capacity (The required embedding capacity of the reversible watermarking schemes is much more than the conventional watermarking schemes as this scheme is capable of embedding the recovery-information and watermark information into the original information). Alattar’s method is a reversible watermarking technique. In Alattar’s method of watermark insertion and extraction watermark is inserted using some mathematical formulae. This method is able to increase the hiding ability. In Alattar’s method, p pixels can hide p-1 bits. Every watermarking scheme is able to recover the watermark as well as authenticating the signal [1]. If, in addition, it is possible to determine that a copy has been made leading to some form of data degradation and/or corruption that can be conveyed through an appropriate analysis, then a scheme should be developed that provides a check on: (i) the authenticity of the data (ii) its fidelity.
2. METHODOLOGY 2.1 Alattar’s Watermark Insertion and Extraction: Alattar’s Watermark Insertion and Extraction method involves insertion of watermark in a signal based on some mathematical formulae. In this method p bits can be hidden by using p+1 pixels. Alattar’s method for insertion and extraction of watermark is explained below: Considering n vector pixels and (n-1) binary values of watermark. Let the vector pixels are (s1 , s2 , s3 , s4 ,……,sn ) and watermark bits are b1 , b2 , b3 ,….,bn-1. Weighted average d1 and the differences d2, d3, d4 are calculated by using the following equation or formula:
,
,
,
. . . . . . . . . . . ,
. . . . . . . . . .
,
Where w1, w2, w3 are predefined weights. In the next step differences are expanded and data bits are embedded into the new differences by using the following equations:
d1’ = d1 , d2’ = 2 × d2 + b1 , d3’ = 2 × d3 + b2 , . . . . . . . . . . ., . . . . . . . . . . ., dn’ = 2 × dn + bn-1 Final embedded pixel values can be obtained by the following equations: s1’ = d1 -
, s2’ = d2’ + s1’ , s3’ = d3’ + s1’ , s4’ = d4’ + s1’
,
. . . . . . . . . . ., . . . . . . . . . . .
,
sn’= dn’ + s1’ Watermark is extracted using the following formulas: , d2’ = s2’ – s1’ , d3’ = s3’ – s1’ , d4’ = s4’- s1’ ,. . . . . . . . . . . , . . . . . . . . . . .
d1’ = dn’ = sn’ – s1’
Watermark data bits are obtained by the following equations: b1 = d2’ - 2×
, b2 = d3’ – 2 ×
, b3 = d4’ – 2 ×
, . . . . . . . . . . . , . . . . . . . . . . . ,bn-1 = dn’ – 2 ×
The original weighted average and difference can be obtained in the following way: d1 = d 1 ’ , d2 =
, d3 =
, d4 =
, . . . . . . . , . . . . . . ,dn=
Finally the original pixels can be received back by using the following equations: s1 = d1 -
, s2 = d2 + s1
,
s3 = d3 + s1 , s4 = d4 + s1 , . . . . . . . . . . ., . . . . . . . . . . ., sn = dn + s1
Example : Suppose there are 4 vector pixels (s1 , s2 , s3 , s4 ) = (110 ,100 , 91 ,78) . Four vector pixels are capable of hiding three binary bits. Let the binary values of watermark data are b1=1, b2=0, b3=1. If w1=w2=w3=w4=1. Therefore, d1=
= 95, d2 = -10 , d3 = -19 , d4 = -32 .
In the next step differences are expanded and data bits are embedded into new differences: d1’ = d1 = 95, d2’ = 2 × d2 + b1 = -19 , d3’ = 2 × d3 + b2 = -38, d4’ = 2 × d4 + b3 = -63. Final embedded pixel values s1’ , s2’ , s3’ ,s4’ can be obtained by the following equations : s1’ = d1 -
= 125 , s2’ = d2’ + s1’ = 106 , s3’ = d3’ + s1’ = 87 , s4’ = d4’ + s1’ = 62 .
Watermark is extracted using the Alattar’s extraction method. To extract the watermark from the watermarked image at first weighted average is calculated: d1’ =
= 95, d2’ = s2’ – s1’ = -19, d3’ = s3’ – s1’ = -38,
d4’ = s4’- s1’ = -63. Watermark data bits are obtained by the following equations: b3 = d4’ – 2 ×
b1 = d2’ - 2×
= 1, b2 = d3’ – 2 ×
= 1.
The original weighted average and difference can be obtained in the following way : d1 = d1’ = 95 , d2 = = -10 , d3 = = -19 , d4 = = -32 . Finally the original pixels can be received back by using the following equations:
= 0,
s1 = d1 -
= 110, s2 = d2 + s1 = 100, s3 = d3 + s1 = 91, s4 = d4 + s1 = 78.
3. PROPOSED METHOD 3.1. Watermark Insertion Step 1. A Heart Sound Sample is converted into 1-D vector. Step 2. A Binary watermark image is converted into converted into 1-D vector Step 3. Size of the watermark signal is calculated. Step 4. Resize the heart signal vector based on the size of the watermark signal (watermark signal +1). Step 5. Watermark signal is inserted within the heart signal using Alattar’s Watermark Insertion Method.
Figure 1: Watermark Insertion using Alattar’s Method 3.2. Watermark Extraction Step 1. To extract the watermark from the watermarked signal Alattar’s Watermark extraction method is used. Step 2. Recovered 1-D watermark vector is converted into 2D image. Step 3. SRN is calculated with the original heart sound and recovered sound.
Figure 2: Watermark extraction based on Alattar’s Watermark Extraction Method
4. RESULT AND DISCUSSIONS MATLAB 7.0.1 Software is extensively used for the study of EEG Signal. Concerned images obtained in the result are shown in Figure 3.
(a)
(b)
(e)
(c)
(f)
(g)
Figure 3: (a) Heart Signal (b) EPR (Watermark Image), (c) Original Heart Signal, (e) Watermarked Signal, (f) Recovered EPR, (g) Recovered Heart Signal
4.1 Signal to Noise Ratio (SNR) Signal to Noise Ratio defines the ratio of the signal power to the noise that causes distortion in the signal. High SNR guarantees clear acquisition of the signal with small amount of distortion. A ratio more than 1:1 signifies more signal than the noise. SNR can be represented using the following equation: SNR = Psig/P no SNR between the original signal and watermarked signal is 37.41. SNR between the original signal and the recovered signal after extracting the watermark from the watermarked signal is 0, which implies there is no change in the recovered signal.
4.2 Correlation Coefficient After secret image embedding process, the similarity of original signal x and watermarked signal x' is measured by the standard correlation coefficient as follows:
x
mn
C
m
x ' ymn y '
n
.......(1)
2 2 xmn x' ymn y ' m n m n
Where y and y' are the discrete wavelet transforms of x and x'. Correlation (corr2) between watermark image and the recovered watermark image is 1. It is observed that the extracted watermark is of good visual quality and the method is best suitable for copyright protection technique.
5. CONCLUSION Since the application of watermark in the Heart Sound signal is a new field of research many methodological aspects is used to insert watermark in the signal and to extract watermark from a signal. Proposed method of using Alattar’s Watermark Insertion and Extraction Technique to insert watermark in a Heart Sound and to extract watermark from that signal is useful in telemedicine application for authenticating source information, verifying signal integrity and proving achieved control over the copy process. In this present work after extracting the watermark from the watermarked signal it can be seen that the SNR of the original Heart Sound signal vs. recovered Heart Sound signal is 0 and that is there is no change between the original signal and the recovered signal. The correlation between the watermark and the extracted watermark is 1 which implies that there is no change between the original watermark and the extracted watermark. These are the advantages of using Alattar’s Watermark insertion and extraction Method for application of watermark in the Heart Sound signal for high security for electronic patient record (EPR).
References 1.
2. 3. 4. 5. 6. 7. 8.
9. 10. 11. 12.
13.
S. Maruthu Perumal, Dr. V.VijayaKumar “A Wavelet Based Digital Watermarking Method using Thresholds on Intermediate Bit Values,” International Journal of Computer Applications (0975-8887), Volume 15 - No.3, February 2011. http://ijns.femto.com.tw/contents/ijns-v2-n3/ijns-2006-v2-n3-p161-170.pdf PPT on Heart Sound Analysis: Theory, Techniques and Applications by Guy Amit, Advanced Research Seminar, May 2004. PPT on Heart Sounds by Don Hudson, D.O., FACEP/ACOEP. Todd R. Reed, Nancy E. Reed, Peter Fritzson,” Heart sound analysis for symptom detection and computer-aided diagnosis,” Simulation Modeling Practice and Theory 12 (2004) 129–146 Faizan Javed, P A Venkatachalam, Ahmad Fadzil M H,” A Signal Processing Module for the Analysis of Heart Sounds and Heart Murmurs”, Journal of Physics: Conference Series 34 (2006) 1098–1105 http://ncalculators.com/statistics/signal-noise-ratio-calculation.htm Mohammad S. Nambakhsh , Alireza Ahamadian , Mohammad Ghavami , Reza S. Dilmaghani , S.Karimi-Fard , “ A Novel Blind Watermarking of ECG Signals on Medical Images Using EZW Algorithms”, Proceeding of the 28th IEEE , EMBS Annual International Conference, New York City, USA , Aug 30 – Sep 3 , 2006 . http://www.ijcst.org/Volume2/Issue3/p7_2_3.pdf G.Coatrieux, L.Lecornu , Members , IEEE ,Ch. Roux, Fellow, IEEE, B.Sankur, Member , IEEE , “A Review of Image Watermarking Applications in Healthcare” A.Giakoumaki, S.Pavlopoulos, D.Koutsoursis, “Secure and efficient health data management through multiple watermarking on medical Images,” Med Bio Eng Comput (2006) 44:619-631, DOI 10.1007/s11517-006-0081-x. Ejima Masataka , Miyazaki Akio , “Digital Watermark Technique Using One-Dimensional Image Signal Obtained by Raster Scanning , Transactions of the Institute of Electronics, information and Communication Engineers. A , Journal Code : S0621A James D. Gordy “Performance Evaluation of Digital Watermarking Algorithms,” A Thesis Submitted to the Faculty of Graduate Studies, The University of Calgary.
