Design of Low Complexity Video WatermarkingAlgorithm based on Integer DCT

Mr. Amit M JoshiDept. of Electronics Engg.

National Institute of TechnologySurat, 395007, India

Email: amj@eced.svnit.ac.in

Dr. R.M.PatrikarDept. of Electronics Engg.

National Institute of TechnologyNagpur, 440010, India

Email: rajendra@computer.org

Dr. Vivekanand MishraDept. of Electronics Engg.

National Institute of TechnologySurat, 395007, India

Email: vive@eced.svnit.ac.in

Abstract—Watermarking is the process of hiding a predefinedpattern or logo into multimedia like image, audio or video ina way that quality and imperceptibility of media is preserved.Predefined pattern or logo represents the identification of theauthor. In recent years, rapid growth in digital multimedia hasbeen noticed. Digital videos are widely exchanged on the internetwith great ease and monetary involment, thus the security ofvideo is main concern in todays digital world. H.264 is currentlyproposed standard for low bit rate video applications. H.264provides high quality than any other previous standardswith implementation of integer transformation. The proposedalgorithm has been implemented for video with Integer basedDiscrete Cosine Transform for higher speed and low complexity.The blind algorithm based on scene change detection schemehas been implemented and verified to check robustness againsttemporal as well as some standard attacks. The algorithmhas been implemented on VIRTEX-4 FPGA board and resultsevident the fact of the watermarking algorithm being efficientin terms of low complexity and high speed.

Keywords-H.264, Histogram, Integer DCT, Robust,Watermarking

I. INTRODUCTION

In todays digital world, most common multimedia objectused frequently is video. Digital video is widely used indifferent application like video-phone, wireless video, sharingvideos on internet, video on demand, video broadcastingand many others [1]. The transition from analog to digitalmakes processing faster. But manipulation of data becomesmore and more easy. With rapid growth of digital technology,the available data can be perfectly copied and rapidlydisseminated at large scale. This has raised concerns overtraditional protection schemes which have been in use forprotection since long time. These schemes are not secure.They no longer serve the purpose of proof for ownership.With the easy access to the editing tool, one can easilygenerate a forgery copy with wrong intention. To addressthese issues, digital watermarking has emerged as a reliablesolution. The digital watermarking, is a method to hidethe identity of author in the multimedia object. It preventsdistribution of illegal and malicious copy. There exists a tradeoff among the parameters of digital video watermarking: datapayload, fidelity, robustness and computation complexity[2].The data payload is the amount of information (number ofbits), which is used to represent the identity of the author

inside video object. The fidelity is defined as presence ofembedded data in imperceptible manner to original video. Theanother critical property is robustness which protects videoagainst some geometrical and frame manipulation attacks. Thecomputational complexity is also an important factor for theimplementation. These all parameters are conflicting in natureand the choice has to be made depending upon the application.The video watermarking is applicable to both compressedand uncompressed domain. Most of the electronic devicesproduce video in some standard formats (like .mp3,.mpgand .flv) which is already in compressed format. The videowatermarking algorithm should have compatibility to thesestandard formats. On the other hand, uncompressed domainwatermarking is directly applied to video frames and suffersthe drawback of large computational complexity where thecompressed stream are first decompressed and then algorithmis applied to raw data and finally, bundled to get watermarkedcompressed bit stream.

Several software implementations of the watermarking al-gorithms are available, but very few attempts have been madetowards hardware implementations. Software implementationof watermarking has been implemented because of their easeand flexibility. Mostly software based watermarking works onoff line mode, where videos are captured through electronicdevices (such as camera) and stored on computer. The wa-termarking algorithm embeds the watermark on it and thenthe videos are distributed. This approach has shortcomingas certain amount of delay get inserted. If attack occurredon the store data before embedding the watermark then itcreates ownership problem for the originator. So there is aneed of real-time watermarking where watermark embeddingunit reside inside the device (such as digital camera) and em-bedding is done directly when information is being captured.The hardware implementation of watermarking have manyadvantages like parallel processing, it also helps to improvespeed and power. This paper has been organized in followingmanner: Sections II has briefing of the literature survey onvideo watermarking, followed by the proposed scheme insection III and the architecture in section IV. The performanceis analyzed in section V and finally concluded in section VI.

978-1-4673-2014-6/12/$31.00 ©2012 IEEE

II. LITERATURE REVIEW

Non-blind algorithm [3] uses temporal feature modulationtechnique to embed the data. In this technique temporalfeature is extracted from each frame and are modulatedaccording to the watermark algorithm. In this algorithm,the selected frames are skipped from the original videoaccording to watermarked codeword. At decoder side, framesare matched with the original video to extract the skippingpattern, from which codeword is estimated. The blind videowatermarking algorithm based on DWT is referred fromthe paper[4]. This algorithm uses stability of low-frequencycomponents in 1D-DWT (1-dimension discrete wavelettransform) for blind frame based video watermarking scheme.The low frequency image is divided into blocks and averagepixel value of each block is adjusted according to watermarkbit. These all have been implemented on software platform.The implementation of video digital watermarking algorithmson hardware are still lacking.

In [5] the authors have presented a 0.18m CMOS technologyimplementation of the Just Another Watermarking System(JAWS) embedder and detector. This watermarking algorithmis a well-known one, basically it works on raw video data thus,allowing the author to concentrate on the watermark processwhereby compression issues not to a concern. JAWS algorithmwas already implemented on a Trimedia TM- 1000 VLIWDSP on a uncompressed real-time video. These DSP resultsare compared with their work. Spread spectrum technique,as described in [6], is simple but very effective method forembedding digital watermark on a compressed domain video.This method assume incoming bit stream in H.261/H.263or MPEG format. In this method, video bit-stream is firstparsed syntactically and data related to header information,motion, texture are separated out in separate buffers. Headerinformation and motion data are kept unchanged and simplyadded to the output bit-stream without any alteration. DCTdata is computed by performing huffman decoding and inversequantization. Watermark data, which is to be embedded intothe stream, is first suitably converted (encryption may be used)so that it is amenable for addition to the DCT data. Watermarkdata is then added to the obtained DCT coefficients carefullyso that it does not result in increased bit-rate. Usually 10 to 20percent of DCT coefficients are altered in this manner. AlteredDCT coefficients are then re-quantized, Huffman coded andthen added to the bit-streams Since last decade, there hasbeen concern over video watermarking in compressed domain.H.264 is current video coding standard which uses IntegerDCT to achieve low complexity with high quality. There isneed to develop video watermarking algorithm which shouldcompatible to integer transform and also provides securityagainst forgery.

III. PROPOSED VIDEO WATERMARKING ALGORITHM

A. Integer Discrete Cosine TransformThe discrete cosine transform (DCT) is very promising

technique used in video coding and has been adapted in vari-

ous video standards such as MPEG-2,MPEG-4,H.263 etc.[7].H.264 is latest standard developed by Joint Video Teamfor different video applications such as mobile video, DVD,broadcasting etc. H.264 provides greatly improved quality atany given bit rate. To achieve low complexity, H.264 standardadopted Integer DCT. The 2-D Integer DCT is implementedwith basic shift and add operation only. This reduces com-putational complexity significantly by avoiding floating pointoperations. The 2- D DCT can be broken into two 1-D DCToperations. The first 1-D DCT is obtained with row processingand transposing the resultant values and then it is feed backto same 1-D DCT second time for column operation.

B. Blind Robust Watermarking based on scene detection

For most of video watermarking application, it is oftendesired to retrieve watermark without access of original con-tent, which is known as blind watermarking scheme. Alsothe algorithm should be robust to sustain attacks on thechannel. The bit plane slicing operation is performed on thewatermark image, the resultant eight different planes of thewatermark image are then used as independent watermark.Each plane is embedded to individual frame of a partic-ular scene. The changes in the scene are detected usinghistogram difference. This approach is useful to withstanddifferent types of temporal attacks such as frame dropping,frame averaging and frame swapping. It involves the basicestimation of AC coefficients from neighboring block DCcoefficients. This estimated AC values are compared withoriginal values to generate the watermark bit. The algorithmdiscussed [8] is software implementation for image which isbased on conventional floating point DCT. To achieve highquality with low complexity, H.264 standard uses integer DCTtransform. The watermarking algorithm should be compatibleto take advantage provided by current standards. The idea isto develop H.264 based blind watermarking algorithm whichuses Integer DCT transformation. The algorithm[8] is extendedfor video using scene detection and is implemented on thehardware to achieve low complexity as well as high speed.The diagram of blind algorithm is shown in Fig. 1

Fig. 1. Watermark Embedding Algorithm

C. Embedding Method

Step 1: The changes in the scene have been detected inthe video by applying the histogram difference method. Thedifferent bit planes of watermarked image are applied todifferent frames of a scene and only the Y component ofYUV format for the frame of video is considered (Assumeinput in YUV format only). The difference of histogram canbe calculated using Eq. (1).

H =∑i,j=0

(Pa(i)− Pb(j))2 (1)

where,Pa= Pixel value of Frame A and Pb= Pixel value ofFrame B.

Step 2: The 8 x 8 integer DCT is applied to each framewhich gives transformed co-efficients to obtain single DCvalue and remaining are 63 AC coefficients.

Step 3: Initially the watermark image is bit plane slicedto get 8 different parts of the watermark. Here each bit-planework as an individual watermark. The watermark embeddingis carried out on the basis of the weight associated with thesebit-planes.

Step 4: The AC values should be predicted from surround-ing neighboring DC blocks as shown below in Fig. 2. Thepredicted AC values are then used to compare with originalvalues for generation of the watermark bit. The equation canbe written as in Eq. (2),(3),(4),(5) and (6).

AC(0, 1) = k1 ∗ (DC4 −DC6)/8 (2)

AC(1, 0) = k1 ∗ (DC2 −DC8)/8 (3)

AC(0, 2) = k2 ∗ (DC4 −DC6 − 2 ∗DC5)/8 (4)

AC(2, 0) = k2 ∗ (DC2 +DC8 − 2 ∗DC5)/8 (5)

AC(1, 1) = k3 ∗ (DC1 +DC9 −DC3 −DC7)/8 (6)

where k1 = (9/8), k2 = (1/4), k3 = (3/16). These constantshas denominator which are expressed as power of 2. Theprediction is suggested by Gonzales [9]. These values areobtained by just shift operation, thereby reducing the overheadof division which certainly results in faster operation.

Fig. 2. Block of watermarking

Step 5: Each bit plane generated in Step 3 is used asindependent watermark. Now according to weight of eachwatermark, bit is embedded on transform co-efficients.For watermark bit 1

Set ACi ≥ AC′

i + delta (7)

For watermark bit 0

Set ACi < AC′

i − delta (8)

In Eq.(7) and (8), ACi is the real value of one of the5 AC components: AC(0,1), AC(1,0), AC(0,2), AC(2,0) andAC(1,1). AC

′

i is the estimated value of ACi by using aboveequations. Delta is a reference threshold. In our experiment,delta can be chosen as any value in the range of 1 to 5. Theidea is to embed different bit planes of the watermark amongdifferent frames of video. Each frame carries some weight oforiginal watermark. If an attack occurs on particular framethen also high probability of retrieving the watermark.

D. Detection Method

The detection method has been carried out using softwareimplementation in MATLAB. There is no requirement ofdevelopment of real time detection. One has to prove his/herauthenticity whenever asked. As proposed algorithm is blind,the original video is not needed for the watermark detection.The histogram method is used for scene detection. IntegerDCT is applied to obtain frames of a particular scene. TheAC values are then estimated from near block DC values.The comparison of the relative value between ACi and itsestimated value AC

′

i is done at detection end. If ACi is largeror equal to AC

′

i , then the extracted bit is 1, otherwise theextracted bit is 0. The bit planes are constructed according toframes of a scene. The resultant watermark is the combinationof different planes obtained from different frames.

IV. ARCHITECTURE DESIGN FOR ALGORITHM

The overall architecture design is shown in below Fig. 3.According to scene detection, the frames of video are storedin ROM1 used as source frame buffer. The 8 bit pixel isgiven to 2-D DCT module. The transformed co-efficients arestored in ROM2 memory. The watermark image is given tobit-plane slice module. The different weights of bit plane aregenerated which is used as watermark bit. The embedding unitembeds the watermark bit to transform coefficients of 2-DDCT module. The output of embedding unit is transform co-efficients having the watermark bit. These values are given toInteger Inverse DCT(IDCT) to get watermarked pixels. The bitplane slicing unit and 2-D DCT are two independent modules.These two processes work simultaneously to achieve parallelprocessing. The pipeline of these two processes also improvethe speed of implementation.

A. Architecture of 2-D DCT

The 2-D DCT module uses pipelined structure where inputsare given parallel and processed at a time, as shown in Fig.4. The input to the 2-D DCT module is the 8 x 8 block ofthe image i.e. 64 pixels with 8 bit width of each block. Eightpixels from one column of 8 x 8 block are given as the inputsto this module in each clock cycle. It takes 8 clock cycles toread 64 input pixels. Each 1-D DCT module uses butterflydiagram to compute the transform. This 1-D DCT is used

Fig. 3. Watermark Embedding Algorithm

to evaluate column transform. These eight inputs are parallelprocessed which generates the eight output each 12 bit wideafter a clock cycle delay. Then these eight elements are givenas the input to the transpose memory. The main function oftranspose memory is to do transpose operation i.e. to write the64 elements column wise and then read those elements rowwise. The total size of the transpose memory is 768 bits. Theoutput of the transpose memory is 12 bit wide. Total eightelements are read and given to the second 1-D DCT module.This 1-D DCT module is used to evaluate row transform. Theoutput of this 1-D DCT is 8 elements each 16 bit wide. Theperformance of 2- D DCT is as shown in following Table. I.The replica of the same process has been used for developmentof Inverse Integer DCT (IDCT).

Fig. 4. Design of 2-D DCT

TABLE IPERFORMANCE OF 2-D DCT

block Process No. of clock cyclecolumn DCT 1-D column processor 8

Transpose Memory column writing/row reading 10row DCT 1-D row processor 2

B. Architecture Design for Bit Plane Slice Module

The watermark image is read with MATLAB and values arestored in ROM3. The bit plane slice module read 8 input andare applied to EX-OR unit. The EX-OR unit performs bitwiseexor operation of incoming pixel with stored values in register1111111. This operation generates weight of bit plane. If theweight is greater than zero then watermark bit is 1 otherwise

the watermark bit is 0. The EXOR unit produces a watermarkbit at each clock cycle. The architecture is shown as in Fig. 5.

Fig. 5. Design of Bit Plane Slice Method

C. Watermark Embedding Unit

The design of watermark embedding unit is shown inFig. 6. The output of 2-D DCT is applied to embedding unitalong with watermark bit. The original values are stored inRAM for comparison. The same values are applied to ACprediction module to estimate AC values. The combinationof adder/subtractor, multiplier and shifter produce estimatedAC values. The comparator compares original values withestimated AC values and embeds 1 bit watermark. The outputdata are given to IDCT to produce watermarked pixel whichare stored in watermarked buffer. The watermarked values areread again through MATLAB to generate watermarked frames.

Fig. 6. Design of Watermark Embedding unit

V. PERFORMANCE ANALYSIS

The algorithm is tested on MATLAB platform. Experimentswere conducted on foreman.avi, consisting of 84 frames eachof size 240 x 320. The 30th number frame of original video isshown in Fig. 7(a). The histogram difference is implementedon MATLAB for scene change detection. The watermarkedMSB plane is used to embed first frame of each scene. Thustotal 5 bits are embedded to every 24 x 24 size of transformedvalues of original image. Payload can be increased with moreprediction of AC values as presented in embedding method. Inour experiment setup, total payload of 150 bits is used for eachframe of original video. The watermark considered is a 64 x

64 lena image shown in Fig. 8. The randomly genearted bitsby pseudo random number from watermark image are usedto embed to original frame. The different bit-planes of thewatermark are shown in Fig. 9 and generated watermarkedvideo is shown in Fig. 7(b). The watermark algorithm istested for different types of attacks as listed in Table. II. Theperformance parameter is a normalized co-efficients denotedas NC. It is defined as correlation of original watermark withextracted watermark. The hardware utilization report of 2-DDCT, 2-D IDCT and watermark embedding unit is shown inTable III. The timing reports of all modules are also presentedin Table IV.

Fig. 7. (a) Original video (b) Watermark video

Fig. 8. Original watermark

Fig. 9. Bit Plane of Watermark Iimage

TABLE IIPERFORMANCE OF ALGORITHM ON A FRAME ATTACK

attacks NC10 percent JPEG compression 0.9789Salt and pepper(density 0.02) 0.9012

Gaussian noise(0 mean and variance 0.01) 0.9423frame insertion 0.9625frame swapping 0.9735frame removal 0.8980

VI. CONCLUSION

The proposed algorithm is applicable to any H.264 basedvideo application. It has the advantage of low complexity dueto integer transform. From Table II, it has been verified thatproposed scheme provides robustness against temporal attacksand is also capable to withstand against frame attacks. Thearchitecture has been designed to take advantages of parallelprocessing and pipelining. Table III showcase the simplicity

TABLE IIISYNTHESIS REPORTS OF VIDEO WATERMARKING ALGORITHM

Resources 2-D DCT Watermark Processor 2-D IDCTSlices (2213/35840) (747/35840) (2234/35840)

Flip-Flops (451/71680) (167/71680) (468/71680)4 input LUTS (3850/71680) (1534/71680) (3840/71680)

IOBs (131/768) (60/768) (131/768)GCLKs (6/32) (2/32) (6/32)

of video algorithm. In Table IV suffices high speed for realtime hardware implemntation.

TABLE IVTIMING REPORTS OF VIDEO WATERMARKING ALGORITHMS

Resources Minimum Time Maximum frequency2-D DCT module 20.815 ns 48.04 MHz

Watermarking process 13.70 ns 74.62 MHz2-D IDCT module 20.723 48.25 MHz

ACKNOWLEDGMENT

I am thankful to the coordinator of SMDP-II Prof. AnandDarji for his unconditional support. My special thanks toSMDP Project Lab, which has provided me the platforms likeISE (Xilinx Tool), Modelsim (Mentor Graphics), MATLABfor experimental performance. I am also thankful to each andeveryone who has been associated with this work for theirsupport and co-operation.

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