Digital image watermarking using dct with high security of

International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online), Special Issue (November, 2013), © IAEME

International Conference on Communication Systems (ICCS-2013) October 18-20, 2013 B K Birla Institute of Engineering & Technology (BKBIET), Pilani, India Page 202

Digital Image Watermarking Using DCT with High Security of Watermark using Image Fusion Technology of

Wavelet Toolbox of MATLAB

Sunil Kr. Sharma1, Divyanshu Varma2

M.Tech Scholar, Department of Electronics & Communication, Bhagwant University, Ajmer, India

[email protected], [email protected]

ABSTRACT: A new area of research to prevent illegal piracy and duplication copying is digital watermarking. Owing to personal computers being applied in many fields and Internet becoming popular and easier to use, most information is transmitted with digital format. Therefore, data copying and back up are more and easier in the World Wide Web and multimedia. The copyright and authentication gradually lose their security [2]. How to protect intellectual property becomes important in technical study and research. Recently, the watermarking technique was proposed to solve the problem of protecting the intellectual property [5]. The imperceptibility and robustness of watermarking can affect Watermarking embedded in frequency domain using FFT or DWT or DCT. In this paper, a watermark embedded in the host image by DCT transform has been proposed [3]. There are several papers using the same manner to embed watermark into middle-band coefficients of DCT block but here we proposed a new approach to provide high security as compared to other developed watermarking tech. using image fusion of wavelet toolbox. KEYWORDS: Digital image watermarking, discrete cosine transform (DCT), Image fusion, Synthesized Image, Histograms.

I. INTRODUCTION The concept of hiding some data into an image, where data is itself an image is known as Digital Image Watermarking. Usually watermarking technique embeds the watermarked data in the main image and all this done by transformation, in which the main image is converted into frequency domain & then merged with the data and the key usually a PN sequence code, text code etc. using watermarking embedding system. As shown in following fig. 1 and fig. 2 shows the reverse process for extraction of watermark using the watermark detection process. In both figures, we require main image and key, So that we can recover the watermark at the receiver end. Due to this process the transmission of main image & key with the watermarked data will increases the complexity, insecurity, piracy etc. To reduce these problems, we propose that the main image & watermarked image both should be combined and transmitted

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ISSN 0976 – 6464(Print) ISSN 0976 – 6472(Online) Special Issue (November, 2013), pp. 202-209 © IAEME: www.iaeme.com/ijecet.asp Journal Impact Factor (2013): 5.8896 (Calculated by GISI) www.jifactor.com

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together so that the main image is not required at the receiver end and this increase the security highly.

Fig. 1: Watermark embedding

Fig. 2: Watermark detection

II. DCT BASED DIGITAL WATERMARKING

DCT is a general orthogonal transform for digital image processing and signal processing with advantages such as high compression ratio, small bit error rate, good information integration ability and good synthetic effect of calculation complexity. One dimensional DCT can be described with the help of (1) and (2) [1], [4]: 퐹(0) =

√∑ 푓(푛) (1)

퐹(푢) = √

√∑ 푓(푛) cos 푢 ( ) (2)

Where F (u) is cosine transform coefficient, u is general frequency variable, u=1, 2, 3…., N-1; if f(x) is M sequence of time domain, x= 1, 2, 3… N-1, one dimensional inverse discrete cosine transform is defined as (3) [1], [4]: 푓(푛) =

√퐹(푢) + √

√∑ 푓(푛) cos 푢 ( ) (3)

Two dimensional DCT can be defined analogously as (4) [1], [4]:

퐶(푢, 푣) = 훼(푢) α(v)∑ ∑ 푓(푥,푦) cos 푢 ( ) cos 푣 ( ) (4)

For u, v =0,1,2,…,N −1 and α(u) and α(v) are defined in (6). The 2D inverse discrete transform is defined as (5) [1], [4]:



푓(푥,푦) = ∑ ∑ 훼(푢) α(v)퐶(푢, 푣) cos 푢 ( ) cos 푣 ( ) (5)

In both equations (4) and (5) α(u) α(v) is defined as

훼(푢),훼(푣) = √

√

, , (6)

DCT allows an image to be broken up into different frequency bands namely the high, middle and low frequency bands thus making it easier to choose the band in which the watermark is to be inserted. The literature survey reveals that mostly the middle frequency bands are chosen because embedding the watermark in a middle frequency band does not scatter the watermark information to most visual important parts of the image i.e. the low frequencies and also it do not overexpose them to removal through compression and noise attacks where high frequency components are targeted [3]. Numerous watermarking techniques based on DCT are proposed. Although some of the watermarking techniques embed the watermark in the DC component, most techniques utilize the comparison of middle band DCT coefficients to embed a single bit of watermark information into a DCT block. The middle-band frequencies (FM) of an 8*8 DCT block can be shown below in fig. 3 [2].

Fig. 3: DCT Regions

DCT block consists of three frequency bands-Low frequency band (FL), High frequency band (FH), mid frequency band (FM). We have chosen FM for embedding the watermark. A. Basic Watermarking Process Algorithm (without key) Common watermarking algorithms usually include two steps: watermark embedding and watermark detection (extraction) [4]. Let f() denote the embedding function, I the original watermark, W the watermark to be embedded, then the watermarked image I’ can be expressed as(7) & shown in fig. 4:

퐼 = 푓(퐼,푊) (7)

Common approach is as follows: Extract a property sequence from original image V = v1, v2… vn, corresponding watermark sequence is X = x1, x2… xn. Embed X into V according to certain model to obtain the adjusted sequence V’ = V + X = v’1, v’2…v’n. Put V’ back and take the place of V, then we get the watermarked image I’. Let E( ) denote the detection function and I’ the image to be examined. Extract the watermark from I’ & extraction shown in fig. 5. The recovered or extracted watermark is given by (8):

푊 = 퐸(퐼 , 퐼) (8)



Fig. 4: Watermarking Embedding Process DCT

Fig. 5: Watermark Extraction Process using DCT



III. PROPOSED TECHNIQUE From above watermarking at the receiver that main image & watermarked image both are required. To reduce such requirement only one image can be send by using image fusion of both images and get the synthesized image using the image fusion technique of wavelet tool box. Basically image fusion is not only a process to combine two images of same type and size but also technique to extract required information from images and then combine them to form a single composite image. The image fusion process can applied in many area of image processing like remote sensing, military surveillance, medical image analysis etc. complete process algorithm shown in following fig. 6 [7] and applied process on our image is shown in fig. 7 using image fusion of MATLAB WAVELET TOOLBOX.

Fig. 6 Image fusion process

Fig. 7 Image fusion using Wavelet toolbox



Fig. 8: Synthesized image

The competitive view of all three images is as shown in fig. 8. This shows the changes in original image due to watermark and then due to fusion of real and watermarked image which gives synthesized output image.

Fig. 9: competitive view of all images

Another competitive view can be shown on the basis of their histograms and cumulative histograms as shown in following figures. The comparison result of all three histograms gives that the histograms of all images are different with little similarity at different points. All histograms made at equal bins (50). As shown in following three figures:



Fig. 10: Histograms of main image

Fig. 11: Histograms of Watermarked image

Fig. 12: Histograms of Synthesized image

IV. CONCLUSION This paper introduces the image fusion for watermark security with embedding of watermark with the help of DCT. In this paper we first insert the watermark into main image then this watermarked image is fused with main image. This synthesized image contains three data main image, watermark data and watermarked image. Due to this way the requirement of main image at detection section will reduces with high security. Here we embed the watermark with the help of DCT but to increase the robustness we may use here DWT also. In the last the histogram shows a comparative look which makes this technique more different and impressive and more expressive. The results of simulation shows this system not only security but also high image quality. The strong capability of embedding signal and anti-attack makes different this algorithm from all other.

REFERENCES [1] Mei Jiansheng, Li Sukang1 and Tan Xiaomei, A Digital Watermarking Algorithm Based On DCT and DWT, Proceedings of the 2009 International Symposium on Web Information Systems and Applications (WISA’09), Nanchang, P. R. China, May 22-24, 2009, pp. 104-107.



[2] Blossom Kaur, Amandeep Kaur, Jasdeep Singh, Steganographic Approach For Hiding Image In DCT Domain, International Journal of Advances in Engineering & Technology, July 2011. [3] Liu Ping Feng, Liang Bin Zheng, Peng Cao, A DWT-DCT Based Blind Watermarking Algorithm for Copyright Protection, Beijing Institute of Graphic Communication, No. Ed0708. [4] Abduljabbar Shaamala, Shahidan M. Abdullah and Azizah A. Manaf, Study of the effect DCT and DWT domains on the imperceptibility and robustness of Genetic watermarking, IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 5, No 2, September 2011. [5] Radhika v. Totla, K.S.Bapat, Comparative Analysis of Watermarking in Digital Images Using DCT& DWT, International Journal of Scientific and Research Publications, Volume 3, Issue 2, February 2013. [6] Chin-Shiuh Shieh, Hsiang-Cheh Huang, Feng-Hsing Wang, Jeng-Shyang Pan, Genetic watermarking based on transform-domain techniques, Pattern Recognition 37 (2004) 555 – 565. [7] Gengming Zhu, and Nong Sang, Watermarking Algorithm Research and Implementation Based on DCT Block, International Journal of Electrical and Computer Engineering 4:10 2009. [8] Franc¸ois Cayre, Caroline Fontaine, and Teddy Furon, Watermarking Security: Theory and Practice, IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL.XX, NO.Y, XYZ 2005. [9] Chiou-Ting Hsu and Ja-Ling Wu, Hidden Digital Watermarks in Images, IEEE Transactions On Image Processing, Vol. 8, No. 1, January 1999. BIOGRAPHY

Sunil Kumar Sharma was born in Ajmer, Rajasthan, India in 1987. He starts his technical career from Birla Technical Training Institute, Pilani by Diploma in Electronics Engineering. He received the Bachelor of Engineering degree in Electronics & Communication Engineering from M.B.M. Engineering College, Jodhpur, India in 2011. He has been completed his P.G. Diploma in Business Administration from SMU-DE, India in 2012. Presently He is working as Guest Lecturer at Govt. Engineering College Ajmer, Ajmer, India & pursuing his Master of Technology in Digital Communication from

Bhagwant University, Ajmer, India. His current research interests focus on Signals & Systems, Signal Processing, Communication systems & Microprocessor.

Divyanshu Varma was born in Ajmer, Rajasthan, India in 1987. He starts his technical career from Birla Technical Training Institute, Pilani by Diploma in Electronics Engineering. He received the Bachelor of Technology degree in Electronics & Communication Engineering from Jaipur National University, Jaipur, India in 2011. He is pursuing his Master of Technology in Digital Communication from Bhagwant University, Ajmer, India. His current research interests focus on Micro-Electronics, Signal Processing and

Communication systems.

Digital image watermarking using dct with high security of

Technology

main image watermarked

synthesized image

host image

digital image processing

transmission of main

watermark information

dct transform

high security of watermark