Multimedia for different purposes3. Generally, a practical watermarking

 Multimediacontent protection has recently become an important issue because ofinsufficient cognizance of intellectual property. Watermarking is one possiblemethod to protect digital assets, and the technology of watermarking hasextended its applications from copyright protection to content indexing, secretcommunication, fingerprinting and many others.The proposed method is a hiding biometric watermark that usesdigital video as a cover file. The recipient needs only process with requiredsteps in order to retrieve the watermark data. The idea of proposed method isbased on hiding the watermark in audio partition of video file instead of video’simage. Also use multiple frequency domains to hide the biometric watermark datausing chaotic stream as key for encrypting the watermark and choose location for hiding.

Theperformance of the proposed algorithm is estimated by used subjective andobjective testes (SNR, PSNR and MSE) with applying simple attack that may attackthe cover file.Experimental result of the algorithm shows good recovering of watermarkcode which is virtually undetectable within video file.Keywords: video watermarking, DCT, DWT, Biometric system, chaotic. I.

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       IntroductionCurrently, Internet and digital media are getting more and morepopular. So, the requirements of secure transmission of data also increased.Various good techniques are proposed and already taken into practice 1. Oneof these techniques is the watermark.

A watermark is a digital code permanentlyembedded into the digital cover content i.e. text, audio or video sequence 2.Watermarking method can be described in the following process.

First, copyright data are abstracted as watermarks and cast onto multimediacarriers by various embedding algorithms. Then, the carriers are distributedvia the computer network or digital storage. If necessary, the carriers areprocessed to detect the existence of a watermark or to extract watermark bitsfor different purposes3.

Generally, a practical watermarking system embeds some copyrightinformation into the host data as a proof of rightful ownership and must meetrequirements: Obviously, Robustness, Imperceptibility, Capacity, and Security 4.Different digital video watermarking algorithms have beenproposed. Video watermarking techniques are classified according to theirworking domain.

Some techniques embed watermark in the spatial domain bymodifying the pixel values in each frame extracted from the video. These methodsare not robust to attacks and common signal distortions. In contrast, othertechniques embed the watermark in the frequency domain, which are comparativelymore robust to distortions2.Digital video is a sequence or collection of consecutive stillimages merging with audio. A watermark can carry any information you canimagine but the amount of the information is limited.

The more information awatermark carries the more vulnerable that information is. Anyway, the amount is absolutely limited by the sizeof particular video sequence2. II. What is biometrics?Biometrics, refers to authentication based on his or herphysiological or behavioral characteristics and its capability to distinguishauthorized and an unauthorized person.

Since biometric characteristics aredistinctive as they cannot be forgotten or lost, the identification person hasto be present physically 56. Among all biometrics such as fingerprint, facial thermogram, handgeometry, face, hand thermogram, iris, retina, voice, signature etc.,Iris-based identification is one of the most mature and proven technique.

Irisis colored part of eye as shown in Fig. 1. Aperson’s two eye iris have different iris pattern, two identical twins alsohave different iris patterns because iris has many feature which distinguishone iris from another.

Primary visible characteristic is the trabecularmeshwork. Iris is not subject to the effects of aging which means it remains ina stable form from about age of one until death. Furthermore, iris recognitionsystems can be non-invasive to their user. The use of glasses or contact lenseshas little effect on the representation of the iris and hence does notinterfere with the recognition technology57.

III.  ChaoticsignalThe chaotic signals are like noise signals but they are completelycertain, that is if we have the primary quantities and the drawn function, theexact amount will be reproduced. The advantages of this signal are as follows 8:I.        The sensitivity to theprimary conditionsThis means a minor change in primary amount will cause significantdifference in subsequent measures. It means if we have a little change in thesignal amount, the final signal will be completely different.

II.      The apparently accidentalfeatureIn comparison with productive accidental natural numberin which the range of the numbers cannot be produced again, the technique used for producing the accidental numberin algorithm based on the chaotic function will prepare the ground that if wehave the primary quantities and the drown function, we can produce the numberagain.III.

     The deterministic workAs the chaotic functions were the accidental manifest, they arecompletely similar. It means as we have the drawn function and the primaryquantities, we can produce and re produce sets of numbers which seemingly haveno system and order. One of the most famous signals which has chaotic featuresis shown in (1), and it is known as the Logistic Map signal,Xn+1=rXn (B-xn)                  (1)in which the Xn will get the numbers between 0,1. The signalshows three different chaotic features in three different ranges on thedivision of  r parameter of which thesignal feature will be the best by considering X0 =0.3.

·        if  r 0,3, then the signal feature in the first 10 repetitionshow some chaos and after that it was fixed , Fig. 2 (a)910·        – if  r  3, 3.57, then thesignal feature in the first 20 repetition show some chaos and after that it wasfixed, Fig. 2(b),·        – if   r   3.

57,4, then thesignal feature is completely chaotic , Fig. 2(c) According to the given description and research requirements forcomplete chaotic feature for video watermarking, the logistic map chaoticsignal with primary value X0=0.3 and r ? 3.57, 4 are used9.                IV.   The related WorksA lot of video watermarking algorithms have been proposed in theliterature employed either in spatial or frequency domain.

One of these methodswas proposed by Mobasseri (2000), who suggest a spatial domain watermarkingscheme for compressed videos. Where Hong et al (2001) have proposed DWT basedalgorithm in which middle frequencies are modified and a flag is generated forextraction process. In the extraction process, another flag is generated fromwatermarked image and compared with the original flag.

In this algorithm,instead of taking watermark image, authors have used generated flag aswatermark. Liu et al (2002) have proposed a wavelet transform-based videowatermarking scheme where multiple information bits are embedded intouncompressed video sequences. Embedding is done in LL sub-band, reducing errorprobabilities of detection via BHC code.

Ge et al (2003) have presented a noveladaptive approach to video watermarking. They take full advantage Waveletpacket transform-based robust video watermarking technique 373 of bothintra-frame and inter-frame information of video content to guarantee theperceptual invisibility and robustness of the watermark. Tsai & Chang(2004) have proposed a novel watermarking scheme for a compressed videosequence via VLC decoding and VLC code substitution.

Zhong & Huang (2006)have presented video watermarking based on spread-spectrum techniques toimprove watermarking robustness. Mirza et al (2007) have proposed a videowatermarking scheme based on Principal Component Analysis 4.V.     The proposed  methodAs we know video file format contain major two part of multimediatypes: image and audio.

It is generated by mixing the two kinds of multimediatypes. The proposed method differs from the typical watermarking scheme. It isbased on hiding watermark data in video’s audio part instead of image one.  Digital watermark is divided into two categories: spatial domainwatermarking technique and frequency domain watermarking techniques.

Thespatial domain methods embed watermark by modifying directly some values ofvideo file. The frequency domain methods will be better to determine perceptioncriterion so as to embed the watermark well 3. Therefore the proposedalgorithm used frequency domain to hide watermark data and in order to achievemore security multiple type of frequency domains with chaotic key are used.In the proposed method, thewatermark is based on biometrics (exactly on iris) to generate the watermarkingcode.

The following sections discuss the proposed video Watermarking in details.A)             The proposed algorithm of embeddingwatermark code:The proposed algorithm can be divided into two basic parts: generatingthe biometric watermark code and hiding it in video file data using chaotic key.·        Generating the biometric watermarking code:Iris region consists of two circles: one for iris sclera boundaryand another for iris pupil boundary. To isolate actual iris region in eyeimage, segmentation is required.

To have segmentation, edge detection, circledetection, eyelid detection are required. Various methods for edge detectionare available. Here, canny edge detection is used to find edges and Houghtransform to find iris and pupil boundaries from the image. CASIA iris image database isused for experimentation. Iris image must be available in sender and receiversides. For more security the watermark is encrypted using chaotic key.

The proposed algorithm of generating the bio-watermarking code isexplained in the following steps: Input: Iris image.Output: Encrypted bio-watermarking code.1)   Begin2)   Chooseiris image.3)   Applyiris segmentation.4)   Take irisdata which is laying under pupil circle. 5)   Applyedge detection using canny filter.

6)   Generatechaotic key.7)   Encryptiris data using the generated chaotic key.8)   End.

Fig. 3 shows the flowcharts of generating the bio-watermark code.               ·        Embedding the watermark in video file using chaotic key:     Input: Video file,Bio-watermark code.

     Output: Watermarked videofile.1)      Begin.2)      Choosevideo file to be cover file.3)      Splitimage and audio in it and consider audio part as a cover.

4)      ApplyDWT on audio part.5)      ApplyDCT on resulted DWT coefficients.6)      Hidethe length of watermark (Len) in first 4 bytes of cover data.7)      Generatechaotic key to be the index of chosen cover data .

8)      Hidewatermark code in cover by exchanging the fourth decimal number after comma incover by another digit of watermark code.9)      Repeatthis step until last digit in watermark code.10)  ApplyDCT inverse, then DWT inverse.11)  Reformat the video cover.12)  End Fig. 4 shows the proposed algorithm of hiding thebiometric watermarking code in video file using chaotic key.

B)            The proposed algorithm of extracting watermark code:Input: The covered video file.   Output: Achieve video file protection or not.1)      Begin.2)      Inputthe covered video file.

3)      Extractaudio part from the covered video file.4)      ApplyDWT on audio part.5)      ApplyDCT on resulted DWT coefficients6)      Extractthe length (Len) of watermark from first 4 byte in cover.

7)      Generatechaotic key(for extracting and decryption operation).8)      Usingthe chaotic key to extract watermark code.9)      Repeatthis step until reaching the length of watermark code.10)   Decrypt the extracted watermark using samechaotic key.11)   Independently… Generate the iris watermarkcode (origin one) by executing the steps of generating the biometric watermark(1 to 5).

12)  Comparethe extracted watermark with the original one. If they are identical ,videofile protection is achieved otherwise the file is not protected.13)  EndFig.5 shows the proposed algorithm ofextracting watermark code.                           VI.   experimentalapplication and resultsA number of videosequences have been tested using the proposed method.

The bio-watermark isextracted from the watermarked video and its robustness is checked by calculatingsome famous measures.Moreover,the proposed method is applied on many iris images obtained from CASIAdatabase. At last the iris code is obtained and hidden in video file. Figs6,7,8 show the experimental steps that are done on iris image to get bio-watermarkcode.                                                                   A number of measures areapplied on it to make sure that the proposed algorithm is strong enough tocarry the watermark safely. Table I.

explain the results of applying standard measures(Correlation, SNR,PSNR and MSE)  to the proposedalgorithm.  table I. theresults of applying standard measures to proposed algorithm File name Correlation SNR PSNR MSE Radar 1 219.3514 75.

586 2.7631e-08 Morale 1 205.74 75.504 2.

8152e-08 Test 1 212.03 75.826 2.6145e-08   The watermarked video was attacked by simpletypes of watermarking attacks. These attacks attempt to damage the embeddedwatermark by modifications of the whole cover without any effort to identifyand isolate the watermark 1112. Adding white noise (Gaussian noise) is appliedto the video cover resulting from the proposed algorithm.

Fig. 9 shows theeffect of adding Gaussian noise to the video cover file with different signalto noise ratio values. While Table II.

explains the output results of adding Gaussiannoise to the video cover .   Table II. Theoutput result of adding gaussian noise to the embedded watermark SNR Correlation MSE 200 1 0 150 1 0 134 0.8720 0.0743 120 0.7956 0.

4149 100 0.1926 3.7147 90 0.

0626 9.2799 75 0.0537 30.

0978  VII.conclusionThe paper propose anefficient method to embed abiometric watermarking in video file. It make use oftwo powerful mathematical transforms: DWT and DCT and applied them on the audio part of video file formatinstead of video’s images. The proposed method use the chaotic sequence inorder to find a video file locations in order to hide bio-watermark on the onehand and the sequence is used  to encryptand decrypt the bio-watermark data on the other. Afterapplying the proposed algorithm, the similarity between the original watermarkand the extracted watermark from video files is measured using correlation,SNR, PSNR and MSE. Also measures are applied on attacked video file usingcorrelation and MSE.

The experimental results show their robustness againstnoise adding; very low noise watermark with expectable SNR values. The obtainedresults give to the proposed algorithm highperformance with robustness in watermarking application in order to achieveprotection to any video file.Reference 1.

Bhaumik Arup , Choi  Minkyu ,Robles Rosslin J. and BalitanesMaricel O. ,” Data Hiding in Video”, International Journal ofDatabase Theory and Application, Vol.

2, No. 2, June 2009, p 9-16 .2. Hood Ankita A. and  Janwe N.

J. ,”Robust Video Watermarking Techniques and Attacks onWatermark – A Review”, International Journal of Computer Trends andTechnology- volume4 Issue1 ,2013, p30-34.3.

Faragallah  Osama S., “Efficient video watermarkingbased on singular value decomposition in the discrete wavelet transformdomain”, International Journal of Electronics and Communications (AE?) , Int.J. Electron. Commun. (AE?) 67 , 2013 , p189– 196 .4. Bhatnagar Gaurav and RamanBalasubrmanian, “Wavelet packet transform-based robust video watermarkingtechnique”, Indian Academy of Sciences , Sadhana  Vol. 37, Part 3,  2012, p 371–388.  5. Al-Gurairi  Maha Abdul-Rhman Hasso,” BiometricIdentification Based on Improved Iris Recognition Techniques”, A Ph. D.Thesis Submitted to The Council of the College of Computer and MathematicalSciences, University of Mosul ,2006.6. Waghmare L.M. and RoselinVanaja, ” Iris Texture Analysis for Security Systems” , InternationalJournal of Computer Applications (0975 – 8887) Volume 64– No.22, 2013, p37-44.7. Dhavale Sunita V. ,”DWT and DCT based Robust Iris Feature Extraction and Recognition Algorithm forBiometric Personal Identification “, International Journal of ComputerApplications (0975– 8887) Volume 40– No.7,  2012, p 33-37.8 Enayatifar R. , MahmoudiF. and Mirzaei K.,” Using the chaotic map in image steganography.International Conference on Information Management and Engineering, 2009 ,p 491-495.9. Saeed  Melad J., ” A New technique based onchaotic steganography and encryption text in  DCT domain for color image”, Journal ofEngineering Science and Technology Vol. 8, No. 5 , 2013, p508 – 520 .10.Ahmed  H.E.,  Kalash, H.M. and Farag Allah, O.S., “Anefficient chaos-based feedback stream cipher (ECBFSC) for image encryption anddecryption”, Informatica, 31(1), 2007 ,p 121-129.11. Ali Dujan Basheer Taha ,”Digital Image Watermarking Techniques For Copyright Protection”, APh. D.  Thesis Submitted to The Councilof the College of Computer Sciences & Mathematics , University of Mosul. ,2004.12.Zlomek  Martin, ” Video Watermarking”,master thesis submitted to Department of Software and  Computer Science Education,  Charles University in Prague , Faculty ofMathematics and Physics, 2007.  


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