A Study of Digital Audio Watermarking for copyright using DCT and LSB Technique

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1 A Study of Digital Audio Watermarking for copyright using DCT and LSB Technique Priyanka Pattanshetti 1, Prof.Shabda Dongaonkar 2 M.E Computer ME student, Dept of Computer Engg, G.H.Raisoni College of Engineering, University of Pune, Pune, Maharashtra Abstract: Digital audio watermarking is an important role in watermarking technique. It provides copyright, verification and protection of digital media. In this new technique the embedded system for audio watermarking is proposed using LSB and Discrete Cosine Transform (DCT) technique. Here first embedding procedure, the image is converted into LSB technique and the audio is divided into equal sized samples and both are converted into DCT and again IDCT is applied to get the watermarked Audio and Image. In extraction procedure the reverse is applied the watermarked audio and image is applied DCT transform and subtracted and applied IDCT to get the original audio. Keywords: Audio, DCT, IDCT, Copyright, Digital Watermarking, LSB INTRODUCTION An audio watermark is an exceptional electronic identifier embedded into an audio signal, usually used to recognize possession of patent. It is related to a watermark on a snap. Watermarking is the system for embedding information into a signal (e.g. pictures, video, audio etc) in a way it is hard to eliminate. If the signal is copied, then the data is also carried. Watermarking has become ever more 44 important to enable copyright guard and rights authentication. With the serve of technology of watermarking in audio it is likely to embed extra data into an audio track. To get this, an audio book, the audio signal of a music recording, or a commercial is somewhat customized in a defined manner. This change is so small that the ear of human being cannot differentiate an auditory difference. Audio watermarking technology thus affords a chance to create copies of a recording which are apparent by viewers as the same to the original but may differ from one to another basis of embedded information. In addition to the ambiguity of the watermark and process security, the other two factors play a vital role. The primary value of data rate of the watermark, is a signal of which the volume of data can be transmitted in a given time period. The further is the strength of the watermark. Robust-ness is an indication how consistently a watermark can be extracted after the inherent signal modifications, an intended attack or after broadcast. The watermarking process is implemented by Music Trace which was found by the EBU (European Broadcasting Union) in requisites of robust-ness. Forms of attack investigated integrated the digital audio coding, repeated filtering of the signal or the analog

2 conversion of signal. This discovered that the watermark can no longer be extracted only when the quality of the audio signal has been significantly ruined as a result of the attack. I. LITERATURE REVIEW Miss Nidhi gupta [1] has stated the new audio technique based on Discrete Cosine Transform (DCT) for copyright protection which is divided into arbitrary segments and energy of each segment is calculated. This method is only not less audible but also more strong against the general signal processing attacks like adding white Gaussian noise, low-pass filter, compression and shearing. Xiang-Yang Wang [5] has stated that the proposed watermarking scheme is inaudible and ro-bust against various signals processing such as noise adding, resampling, quantization, random cropping, and MPEG-1 Layer III (MP3) compression. Xian yang Wa [2] has stated that the watermark embedding depth is determined according to the audio own characteristics, which improve the working performance of the whole audio watermark. It also improves imperceptibility and robustness performance of watermarking. Mohammad Ibrahim Khan[3] has stated that the DCT coefficients are split into a permanent number of subsections and the power of each subsection is considered. Next, watermark is produce to image by image processing algorithm. Watermarks are then set in into chosen peaks of largest energy subsection. To estimate the performance of the audio watermarking method, the feature tests with Signal to Noise ratio (SNR) and Bit Error Rate (BER) are concluded. Yekta Said Can [4] has stated that a watermarking audio scheme is based on technique called Spread Spectrum to embedding the watermark. This technique doesn t needs the carrier signal which is original audio while retrieving watermark using the blind retrieving audio watermark. 45 Huan Zhao [6] has stated that a novel blind audio watermarking algorithm, which combined Discrete Wavelet Transform (DWT) with Singular Value Decomposition (SVD). Sandeep Kumar U [7] has stated that DWT- ECC processor with watermarking a secure image algorithm is planned. The elliptic curve cryptography (ECC) have been recognized and engaged as a competent and proper plan for public key cryptographic systems. LSB (Least Significant Bit) uses image and a algorithm Steganography is employed to code the message in the figure and is apply during discrete wavelet transform (DWT) on coverage image. The high volume data in image is hidden and also is perceivable in image while providing strong backbone for security. Tejash Lad [8] ] in this paper audio watermarking is a technique the information copyright is hided into audio signal without affecting the original quality of audio signal and it proposes audio watermarking technique to embed and extract procedure in DCT domain. Ashima Wadhwa [9] in this paper has 4 main trends for development of steganography

3 is: digital media linguistic steganography, network steganography and file system steganography. In digital media steganography use of images, text files, videos and audio as carrier. Gaurav Saini [10] has stated that the secret communication in to an audio file is embedded with an other audio carrier file (.wav). In the transmitted end the output would be like to secret message embedded with carrier inside. In the 2 nd stage it uses a more influential customized LSB (Least Significant Bit) Method to code the message into audio. It performs bit level operation to encode the message. In the third level it uses the AES algorithm to increase the audio bit size and also to improve the security. The excellence of sound depends on the size of the audio which the user selects and time-span of the message. Faizur Rahman[11] this paper states that features like harmony, timbre, mood, pitch temporal, rhythmic, genre and instrument several that can be extracted from the music. Usual musical audio feature extraction is utilized for identifying type and its particular consumption must be passed out in watermarking in audio so as to develop the performance. Jyoti Rani[12],this paper states that comparing two techniques Spread-Spectrum techniques and Least Significant Bit (LSB) and find one which for the most part suitable for the image safety against the malicious, privacy and counterfeiting manipulations of the image. Pavan Kumar Kota [13] states that a performance of digital watermarking of an audio signal with image is made with various algorithms and a relative study is obtained. The performance is organized using both frequency domain and spatial for the job of 46 data hiding. The concepts of Discrete cosine transform (DCT), Least significant bit (LSB) substitution, Discrete wavelet transform (DWT), echo hiding and high frequency tone. Mean Square Error (MSE), Peak Signal-to- Noise Ratio (PSNR) and Signal-to-Noise Ratio (SNR) are the performance metrics used for the study. Usha B.A [14] states that has being used the deliberate on FFBP-NN. Steganography method is used the feature extracted from Discrete Cosine Transforms (DCT) coefficients along with FFBP-NN classifier is evaluated, using an image dataset of 30 images,containing 4 classes and each class having 5 images. Khalid A. Darabkh [15] states that In capable audio watermarking embedding and extraction technique, which use Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT), in which a new for-mation of details sub-bands is proposed. Kamlesh.C.Badhe[16], states that execution of watermarking in audio in images using families of wavelet is explained. The algorithm is based on breakdown of images using Haar wavelet basis, Daubechies wavelet, Biorthogonal wavelet, Reverse biorthogonal wavelet and Discrete approximation of Meyer wavelet. II. METHODOLOGY A. LSB The least significant bit (LSB) technique is used for embedding information into an image. The LSB technique is that inside of a cover image pixels are changed by bits of the secret message. Although the digit

4 was embedded into the first 8 bytes of the grid, the 1 to 4 least bits essential to be transformed according to the embedded message. On the avg, only part of the bits in an image will be customized to hide an undisclosed message using a cover image. Because the quality of the Watermarked image is low, less than over the 4-bit LSB, changing the pixel of LSB and results in tiny changes in the intensity of the colours. These changes cannot be retrieved by the human visibility system. However, a passive attacker can easily extract the changed bits, since; it has performed very simple operation. EXAMPLE: B. DCT Discrete Cosine Transform technique: The standard and largely accepted field (domain) for audio processing of DCT or Discrete Cosine Transform. In this system watermark bits of data are widen over the host signal so that the strength of the embedded signal is improved. In this technique the low frequency or components are there so as embedded with which gives the DCT better result beside the different attacks. For a One-D discrete signal the length of N, Discrete Cosine Transform represented as D -- (1) Where m = 0, 1, 2,..., N 1. For the One-D signal, inverse DCT is represented as --- (2) In (1) and (2), for m = 0, 1, 2, N 1, a (m) III. PROPOSED METHOD A. LSB Algorithm 1) Embedding Process 1. Obtain the Input Image called Imp 2. Obtain the Watermark image called eimg 3. eimg to OneeD bit format 4. Recognize the size of image called (e,s) 5. For I =1 to e 6. For j=1 to s 7. WatermarkedImage(img,I,j,8)=eimg (k) 8. l=l+1; 9. If (l>length(eimg) 10. Exit 11. Return WatermarkedImage 12. Exit 2) Extraction Process 1. Read the Watermark Image WatermarkedImage 2. Read the message size 47

5 3. Identify image size called (e, s) 4. For I =1 to e 5. For j=1 to s 6. Message (n)=watermarkedimage(i,j,8) 7. l=l+1; 8. If (n > size) 9. Exit 10. Return Message 11. Exit B. DCT Algorithm 1) Embedding Process 1. Obtain the Input Image called Img 2. Obtain the Watermarked image called eimg 3. Define the blocksize called blck and the frequency threshold 4. Convert eimg to OneeD bit format 5. For a=1length(waimage) 6. Perform the DCT for the particular block and return the block DCT. 7. If (waimage(a)=0) 8. Exchange (swap) the Ascending order the DCT block values 9. Else 10. Exchange in Descending order the DCT block values 11. Carry out the Analysis of Frequency for the block and at extract DCT Block hide data. 12. Do the IDCT over the image and show it as watermarked block 13. Return WatermarkedImage 14. Exit 2) Extraction Process 1. Get the Watermarked representation called dctimage 2. Get the message size called size 3. Define DCT Block size called blck 4. For n=1 to size 5. Perform the DCT over the (x,y) Block DCT(img,x,y) 6. Move to nxt block 7. Compare the DCT Block frequency values set the high value to 1 and low to 0 8.Message=MessageExtract(DCTBlockValue,high,low) 9. Return Message 10. Exit A. Embedding Procedure 48

6 Original Audio LSB Image LSB Divide audio signal in equal Convert to 2 Dimensional DCT Original Image Watermark Audio+ Image Inverse DCT Embedded Audio+Ima ge B. Extraction Process Fig 1: Proposed block diagram for Embedded Procedure Original Audio DCT Watermarked or Embedded Audio+Image DCT Subtract original audio and Audio+ image Image Fig 2: Proposed block diagram Inverse for DCT Extraction Procedure Extracted Image Fig 2: Proposed block diagram for Extraction Procedure 49

7 V. CONCLUSION This paper provided a study of a digital audio watermarking using DCT transform and LSB which is robust and effective algorithm as the audio signal retrieved is clearly audible. REFERENCES [1]. A DCT Based Watermarking Method For Copyright Protection, International Journal for Technological Research in Engineering Volume 1, Issue 8 April ISSN (On- Line) by Miss Nidhi Gupta, Dr. S.A.Ladhake. [2] A New Adaptive Digital Audio Based on Support Vector Regression, IEEE Transactions on AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 15, NO. 8, NOVEMBER /$ IEEE by Xian yang Wang, Wei Qi, and Panpan Niu. [3] A New Audio Watermarking Method Based on Discrete Cosine Transform with A Gray Image, International Journal of Computer Science & Information Technology (IJCSIT) Vol 4, No 4, August 2012, DOI : /ijcsit by Md. Iqbal Hasan Sarker2, Md.Hasan Furhad, Mohammad Ibrahim Khan and Kaushik Deb3 [4] A Novel Spread Spectrum Digital Audio Watermarking Technique, Journal of Advances in Computer Networks, Vol. 2, No. 1, March 2014, DOI: /JACN.2014.V2.71, by Fatih Alagoz, Melih Evren Burus and Yekta Said Can, [5] A Novel Synchronization Invariant Audio Watermarking Scheme Based on DWT and DCT, IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 54, NO. 12, DECEMBER 2006, X/$ IEEE, by Xiang-Yang Wang and Hong Zhao. [6] A Robust Audio Watermarking Algorithm Based on SVD-DWT, ELEKTRONIKA IR ELEKTROTECHNIKA, ISSN , VOL. 20, NO. 1, 2014, by Huan Zhao, Fei Wang, Zuo Chen, Jun Liu [7] A Secured Algorithm Based On ECC and DWT with Watermarking, (An ISO 3297: 2007 Certified Organization) Vol. 2, Issue 5, May 2014, SSN(Online): , International Journal of Innovative Research in Computer and Communication Engineering by Sandeep Kumar U, Y. Manjula, Dr.K.B.Shivakumar, Dr.M.Z.Kurian. [8] A Study of Audio Watermarking Technique in DCT Domain, 2014 International Journal of Engineering Development and Research Volume 2, Issue 1 ISSN: , by Tejash Lad, Kaushal Doshi [9] A Survey on Audio Steganography Techniques for Digital Data Security, International Journal of Advanced Research in Computer Science and Software Engineering, 50

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