Improved Performance Of Spread Spectrum Audio

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International Journal of Engineering, Management & Sciences (IJEMS)ISSN-2348 –3733, Volume -1, Issue-7, July 2014Improved Performance of Spread Spectrum AudioWatermarking Technique, by reducing the CostFunction Using 6 Bipolar VectorsSanjay Meena,Vijay Kumar Sharma Abstract— Digital watermarking is an approach to insertinginvisible or visible marks into a digital multimedia data forfurther detection of correct ownership at the later stages. Mostof the watermarking techniques focus on image and audio file,and several are related to audio file. The proposed workconcentrates on improving the performance of spread spectrumaudio watermarking technique. Audio watermarking is theprocess of embedding a watermark signal into an audio signalfor proof of rightful ownership. This process is rather difficultdue to the high sensitivity of the Human Auditory System(HAS). Among all watermarking technique, spread spectrumtechniques are widely used as audio watermarking because oftheir robustness and imperceptiveness of watermarking. Theproposed technique is based upon the False positive and Falsenegative probability. False negative probability is a probabilityof non detection of watermark. Whereas, the false positiveprobability is the probability of detection of a watermark foundin a non-watermarked host signal. The work will reduce the costfunction using 6 bipolar Vector and generate the algorithm.The comparative results of PSNR and SNR values calculatedfor different parameters of audio and text files.Index Terms—SNR, Spread Spectrum,Cryptography.I. INTRODUCTIONToday the fast growing internet and multimedia technologies,each and every thing is getting digital. So the security is themain concern in electronic communication. So there is need todevelop more secure steganography, cryptography andwatermarking techniques, more resist to attack. Therefore,field of digital watermarking has grown extremely fast [1].Digital watermarking is based on the principle of embeddingsome secondary information into a digital signal that cannotbe detectable by its intended recipient. For instance, in thecase of multimedia watermarking, there will be no presence ofany visible or audible distortions in the hidden signal. Withthe help of embedded signals, as invisible tag can be attachedto digital file. Watermarking have shown its powerful calibrein solving the growing problem of identification of digitalproperty [2]. Security, encryption and watermarking can becategorized as shown in figure1.FIG. 1. CLASSIFICATION OF DIFFERENT SECURITY SYSTEM, FORINFORMATION HIDINGSteganography hide the facts which are sending to the enduser. Watermarking is similar, but has a completely differentpurpose. Watermarking is the process of embeddinginformation on the multimedia [3][4].A relation between various data hiding techniques andrelated parameters is illustrated below in table1.Table 1Comparison of Steganography, Cryptography andWatermarkingManuscript received July 20, 2014Sanjay Meena, M.Tech Scholar, Department of Computer Science,Rajasthan institute of Engineering & Technology, JaipurVijay Kumar Sharma, Department of Computer Science, Rajasthaninstitute of Engineering & Technology, Jaipur13www.alliedjournals.com

Improved Performance of Spread Spectrum Audio Watermarking Technique, by reducing the Cost Function Using 6Bipolar VectorsWatermarking is the process of embedding informationinto a digital signal in such a way that is difficult to removeand to counterfeit. The signal may be audio, image or video.Several watermarks can be carried by a single signal at thesame time. Fig 1.2 provides an illustration of a generic audiowatermarking process of various signal types.Fig. 2. Flow Diagram of Proposed techniqueFig. 1 General Audio Watermarking ProcessII. PROPOSED TECHNIQUEThe implementation of audio watermarking is done throughthe spread spectrum watermarking technique [1][5].The basicspread spectrum technique is upgraded to an improvedversion, which will provide robustness, ensuring complianceto the copyright laws. This will also minimize the costfunction with the help of false negative and false positiveprobabilities.The improved technique works similar to the basic spreadspectrum watermarking technique. The working of the newdeveloped technique is explained thoroughly in the phasesbelow. All the programming and results are carried out in theMatlab R2013a. The block diagram is showing the completediagrammatic procedure going in the implementation stages.141. In the first step an input audio file is taken.2. In the next step insert input message in the form ofbi-Polar variables3. Do the Down-sampling of the audio file into“blocks”4. Apply Fast Fourier Transformation for finding thespectrum of each “block” of input audio file.5. Embed Watermark into spectrum of “blocked”form of input Audio file.6. Repeat step 5 till the whole watermark is insertedand then go to step7.7. Apply Inverse Fast Fourier Transformation to getaudio signal.8. End.The proposed technique provide robust audiowatermarking, the technique is apply on the 90 ms ofblock. The excremental results show the strength ofproposed technique.III. RESULT ANALYSISThe implementation of the proposed technique use thewww.alliedjournals.com

International Journal of Engineering, Management & Sciences (IJEMS)ISSN-2348 –3733, Volume -1, Issue-7, July 2014SignalProcessing,SpectralAnalysis,and Fig.6. After embedding text “Hello” waveform of Audio fileManipulation functions tools of Matlab, whichincludes the FFT and IFFT transforms, but also usenew raw program code for development.Fig.3. Original Audio file WaveformFig. 7. After extraction of text “Hello” from Audio fileTo test the imperceptibility of watermarked signal thesignal to noise ratio (SNR) between the original signal and thewatermarked signal is computed using below equation.Different experiments were conducted to prove that theproposed method of embedding audio file. The followingexperiments were conducted with same and different audiofile.1. Same audio file is embedded with different text file withvarying text content sizes.2. Different audio files of are taken and embedded withsame text content.The observed results during experimentation are presentedin table 2 and table 3.The SNR is signal to noise ratio, which is measured asFig. 4. Text for embedding into Audio fileTable 2SNR/PSNR values for same audio file with different textFig.5. Text “Hello”for embedding into Audio file15www.alliedjournals.com

Improved Performance of Spread Spectrum Audio Watermarking Technique, by reducing the Cost Function Using 6Bipolar VectorsFig.8. Comparison graph based on table 2As the file size is increases the SNR and PSNR values reduce,indicating that weak noise is not harmful to the changed bits athigher layers.Table 3SNR/PSNR values for different audio file with same textFig 9 Comparison graph based on table 3figure 9 shows that the data size is increase the only SNRvalue change the PSNR values remain same. It can also beconcluded in a straight way from figure 9 that the size of audiofile is increase the PSNR does not change.REFERENCES[1]. M. Davarynejad, S. Sedghi, M. Bahrepour, C.W. Ahn, M. Akbarzadehand C. A. Coello Coello, “Detecting Hidden Information from WatermarkedSignal using Granulation Based Fitness Approximation, Applications of SoftComputing: From Theory to Praxis, Springer, Series: Advances in Intelligent16www.alliedjournals.com

International Journal of Engineering, Management & Sciences (IJEMS)ISSN-2348 –3733, Volume -1, Issue-7, July 2014and Soft Computing” Vol. 58/2009, ISBN 978-3-540-89618-0, pp. 463-472,2009.[2]. S. Katzenbeisser and F. A. P. Petitcolas, “Hiding Techniques forSteganography and Digital Watermarking”, S. Katzenbeisser and F. A. P.Petitcolas, Eds. Boston, MA: Artech House, 2000 . Volume ISBN1-58053-035-4[3]. Transactions on K. Su, D. Kundur, and D. Hatzinakos, “StatisticalInvisibility for Collusion-resistant Digital Video Watermarking,” IEEEMultimedia 2004 .IEEE Transactions On Multimedia,VOL.7,No.1 Feburary2005[4]. K. Su, D. Kundur, and D. Hatzinakos, “Spatially LocalizedImage-dependent Watermarking for Statistical Invisibility and CollusionResistance,” IEEE Transactions on Multimedia 2004 . Volume 7 Issue 1,February 2005.[5]. I. Cox, M. Miller, and J. Bloom, “Digital watermarking,” MorganKaufmann Publishers”, Oct. 2001, ISBN 1-55860- 714-5.17www.alliedjournals.com

Fig.5. Text “Hello”for embedding into Audio file Fig.6. After embedding text “Hello” waveform of Audio file Fig. 7. After extraction of text “Hello” from Audio file To test the imperceptibility of watermarked signal the signal to noise ratio (SNR) between the original signal and th

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