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A source channel coding approach to digital image protection and self-recovery

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Final Year IEEE Projects for BE, B.Tech, ME, M.Tech,M.Sc, MCA & Diploma Students latest Java, .Net, Matlab, NS2, Android, Embedded,Mechanical, Robtics, VLSI, Power Electronics, IEEE projects are given absolutely complete working product and document providing with real time Software & Embedded training......

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A source channel coding approach to digital image protection and self-recovery

  1. 1. OUR OFFICES @ CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com A SOURCE-CHANNEL CODING APPROACH TO DIGITAL IMAGE PROTECTION AND SELF-RECOVERY By A PROJECT REPORT Submitted to the Department of electronics &communication Engineering in the FACULTY OF ENGINEERING & TECHNOLOGY In partial fulfillment of the requirements for the award of the degree Of MASTER OF TECHNOLOGY IN ELECTRONICS &COMMUNICATION ENGINEERING APRIL 2016
  2. 2. OUR OFFICES @ CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com CERTIFICATE Certified that this project report titled “A Source-Channel Coding Approach to Digital Image Protection and Self-Recovery” is the bonafide work of Mr. _____________Who carried out the research under my supervision Certified further, that to the best of my knowledge the work reported herein does not form part of any other project report or dissertation on the basis of which a degree or award was conferred on an earlier occasion on this or any other candidate. Signature of the Guide Signature of the H.O.D Name Name
  3. 3. OUR OFFICES @ CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com DECLARATION I hereby declare that the project work entitled “A Source-Channel Coding Approach to Digital Image Protection and Self-Recovery” Submitted to BHARATHIDASAN UNIVERSITY in partial fulfillment of the requirement for the award of the Degree of MASTER OF APPLIED ELECTRONICS is a record of original work done by me the guidance of Prof.A.Vinayagam M.Sc., M.Phil., M.E., to the best of my knowledge, the work reported here is not a part of any other thesis or work on the basis of which a degree or award was conferred on an earlier occasion to me or any other candidate. (Student Name) (Reg.No) Place: Date:
  4. 4. OUR OFFICES @ CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com ACKNOWLEDGEMENT I am extremely glad to present my project “A Source-Channel Coding Approach to Digital Image Protection and Self-Recovery” which is a part of my curriculum of third semester Master of Science in Computer science. I take this opportunity to express my sincere gratitude to those who helped me in bringing out this project work. I would like to express my Director,Dr. K. ANANDAN, M.A.(Eco.), M.Ed., M.Phil.,(Edn.), PGDCA., CGT., M.A.(Psy.)of who had given me an opportunity to undertake this project. I am highly indebted to Co-OrdinatorProf. Muniappan Department of Physics and thank from my deep heart for her valuable comments I received through my project. I wish to express my deep sense of gratitude to my guide Prof. A.Vinayagam M.Sc., M.Phil., M.E., for her immense help and encouragement for successful completion of this project. I also express my sincere thanks to the all the staff members of Computer science for their kind advice. And last, but not the least, I express my deep gratitude to my parents and friends for their encouragement and support throughout the project.
  5. 5. OUR OFFICES @ CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com ABSTRACT: Watermarking algorithms have been widely applied to the field of image forensics recently. One of these very forensic applications is the protection of images against tampering. For this urpose, we need to design a watermarking algorithm fulfilling two purposes in case of image tampering: 1) detecting the tampered area of the received image and 2) recovering the lost information in the tampered zones. State-of-the-art techniques accomplish these tasks using watermarks consisting of check bits and reference bits. Check bits are used for tampering detection, whereas reference bits carry information about the whole image. The problem of recovering the lost reference bits still stands. This paper is aimed at showing that having the tampering location known, image tampering can be modeled and dealt with as an erasure error. Therefore, an appropriate design of channel code can protect the reference bits against tampering. In the present proposed method, the total watermark bit-budget is dedicated to three groups: 1) source encoder output bits; 2) channel code parity bits; and 3) check bits. In watermark embedding phase, the original image is source coded and the output bit stream is protected using appropriate channel encoder. For image recovery, erasure locations detected by check bits help channel erasure decoder to retrieve the original source encoded image. Experimental results show that our proposed scheme significantly outperforms recent techniques in terms of image quality for both watermarked and recovered image. The watermarked image quality gain is achieved through spending less bit-budget on watermark, while image recovery quality is considerably improved as a consequence of consistent performance of designed source and channel codes.
  6. 6. OUR OFFICES @ CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com INTRODUCTION: Digital imaging has been rapidly developing in last two decades, and digital multimedia products are utilized in countless applications nowadays. As a consequence of this expansive development, popular and low-cost access to image editing applications challenges the integrity of digital images. On the other hand, sophisticated techniques are required to guarantee the integrity of an image or protect it against malicious modifications. One common approach is to use the hash of the original image. The receiver declares the image as unaltered if the hash output is the same as the one transmitted from the original image. Image integrity verification through hash requires a secure channel that must be reused for each image transmission. Since such a channel might be unavailable, a more applicable approach is to embed the verification data into image itself, which is referred to as fragile watermarking. Fragile watermarks can be used for both authentication of the received image and localization of tampered zone in case of malicious modifications (tampering localization), and recovering the image information in the lost area (error concealment). Inceptive fragile watermarking techniques aim only to verify the integrity of image or locate the tampered area with limited robustness against image processing modifi- cations .More recent methods in the field of tampering detection achieve the perfect 100% localization using watermarks robust against wide variety of attacks, On the other hand, watermarking algorithms with the purpose of error concealment aim to restore information in the previously-detected tampered parts.Another class of watermarking techniques takes one step further and aims to accomplish both tasks of tampering localization and error concealment via a single watermark. This self-recovery watermarking trend, initiated by , has recently attracted growing interest. The problem of image self-recovery has been approached in numerous ways. In conventional error control coding schemes are adopted for localization and restoration. Several methods embed a representation of an original image into itself for the sake of self-recovery. In discrete cosine transform (DCT) coefficients or reduced color-depth version of the host image is embedded in the least significant bits (LSB) of the original image. This representation of the original image can also be the first few DCT coefficients of each block a binary image generated from the difference between the host image and its chaotic pattern the hash of the original image watermark derived from approximation coeffi- cients of its wavelet transform, a vector quantized
  7. 7. OUR OFFICES @ CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com or halftone version of the original image. Fragile watermarks may also be designed for specific purposes, such as binary images, JPEG compressed images, colored images, compression- resistant or croppingresistant applications. Watermark bits in self-recovery methods are conventionally fallen into two categories, namely check bits and reference bits. The check bits are used to localize the tampered blocks, while the reference bits are employed to restore the original image in the tampered area. Normally for the sake of content restoration, reference bits of a certain block are always embedded into another one. Nevertheless, in some of these methods content recovery may fail because both the original block and the one containing its reference bits are detected as tampered. This is called tampering problem.To tackle this challenge, recent techniques spread the representation data of one block over entire imagel, On the other hand, there exists another problem of watermark waste, that is, where both original data and its reference bits are available. For instance, suggests a dual watermarking scheme where watermarked image carries two copies of content data for each block, in order to leave a chance of restoration when one copy is lost because of tampering.It should be kept in the mind that when both copies and original data survive the tampering, the watermark budget which could help the restoration of other tampered blocks is wasted. The most recent methods also deal with the watermark waste problem by offering schemes in which the content information is derived from several blocks In our proposed algorithm, reference bits are the source coded image. This data is derived from and then scattered over the whole image to overcome both tampering and waste problems. The problem of image self-recovery is about finding an appropriate trade-off between these three parameters:the watermarked image quality, content recovery quality,and tolerable tampering rate (TTR). The size of watermarkdetermines the amount of imposed distortion and the quality of the watermarked image. On the other hand, more watermark bits are required to achieve higher TTR or better quality in the recovered area. Recent methods generally dedicate three LSB of the original image to watermark embedding and keep remaining five most significant bits (MSB) unchanged. As examples of this trade-off, some methods provide almost error free restoration at the expense of very limited TTR or a very low quality of the watermarked image .
  8. 8. OUR OFFICES @ CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com On the other side, a few techniques sacrifice the restoration quality to deal with high tampering rate. Content adaptive schemes have recently been proposed to compromise between TTR and restoration quality based on specific application. This trade-off is also observed as constant versus flexible restoration. Reconstruction quality decays as tampering rate increases for flexible methods, whereas constant fidelity algorithms offer constant quality of reconstruction for tampering up to a certain limit at the expense of failing to restore tampered area beyond that limit We approach this trade-off in our image self-recovery algorithm using these two key ideas: i) Modeling image representation and reference bit generation as a source coding problem; ii) Modeling the tampering as an erasure channel while handling it with proper channel coding. The location of tampered areas being identified through check bits, tampering can be modeled as an erasure channel, where the locations of occurring errors are known to the receiver. Erasure modeling of tampering has been recently offered and exploited in and where the authors apply fountain codes, to deal with it. It should be added that when one block is marked as tampered, all its carrying reference bits are missed. We would suggest Reed-Solomon (RS) codes, with large encoding blocks and over large Galva fields to solve the erasure problem. Moreover, we treat the challenge of finding some representation of the original image as a source coding problem. We apply the wavelet transform and set partitioning in hierarchical transforms (SPIHT) source encoding method ,to efficiently compress the original image. Therefore, the watermark consists of three parts in our algorithm: source code bits, channel code parity bits and check bits. Source code bits which act asthe reference bits are the bit stream of the SPIHT-compressed original image at a desired rate. In order to survive tampering erasure, the reference bits are channel coded to produce channel code bits. Check bits are used at the receiver to determine the erasure location for the channel erasure decoder. The output of channel decoder is source decoded to find the compressed version of the original image. This work shows that by choosing appropriate parameters for source and channel encoding, our algorithm outperforms existing methods in the same watermark payload of three bits per pixel (bpp). Nevertheless, since the watermark artifacts are significant for embedding in three LSB, we would recommend two-LSB version of our algorithm and show that its performance is still remarkable. This paper proceeds as follows. Section II briefly reviews some
  9. 9. OUR OFFICES @ CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com of the state-of-the-art self-embedding schemes. Section III presents our image self-recovery algorithm in general, while its components are explained in details in the subsequent sections. Section IV introduces SPIHT as our chosen source coding method. The RS channel coding is investigated in Section V as our choice for channel encoding to combat the channel erasure. Check bit generation is explained in Section VI. Section VII describes an example of parameter selection based on required performance. Experimental results are presented and discussed in Section VIII, and Section IX concludes the paper.
  10. 10. OUR OFFICES @ CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com CONCLUSION: In this paper, we introduced a watermarking scheme to protect images against tampering. The watermark bit-budget falls into three parts, check bits, source encoder output bits, and channel encoder parity bits. The original image is source coded using SPIHT compression algorithm. The source encoder output bit stream is channel coded using RS code of a required rate and over appropriate field. Since image tampering affects a burst of bits, the RS codes over large Galva fields are wise choices. On the other hand, check bits support the receiver in locating the tampered blocks. Therefore, the receiver knows the exact location of erroneous bits. Tampering is modeled as an erasure error in this way. Thus, we need an RS channel erasure decoder for image recovery at the receiver. The lengths of the channel encoder input and output blocks are also taken as long as possible to achieve the best performance. Setting up the RS channel codes over G F(2 t +1) instead of G(2 t ) is another suggestion of this paper which greatly simplifies the complexity of channel encoder and decoder implementation. It is shown that our watermarking scheme which replaces only two LSB of an image, efficiently recovers the tampering up to 33% without leaving any noticeable distortion. However, if we implement our algorithm using 3 LSB, it totally outperforms the state- of-the-art methods using the same three LSB for watermarking. It should be noted that albeit the proposed scheme is just implemented for two certain sets of parameters, it can be flexibly adapted to different applications with different purposes, thanks to adaptive rate adjustment capability of applied source and channel codes.
  11. 11. OUR OFFICES @ CHENNAI/ TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE / BANGALORE / HYDRABAD CELL: +91 9894917187 | 875487 1111 / 2111 / 3111 / 4111 / 5111 / 6111 ECWAY TECHNOLOGIES IEEE SOFTWARE | EMBEDDED | MECHANICAL | ROBOTICS PROJECTS DEVELOPMENT Visit: www.ecwaytechnologies.com | www.ecwayprojects.com Mail to: ecwaytechnologies@gmail.com REFERENCES: [1] A. Swaminathan, Y. Mao, and M. Wu, “Robust and secure image ,hashing,” IEEE Trans. Inf. Forensics Security, vol. 1, no. 2, pp. 215–230,Jun. 2006. [2] S. Roy and Q. Sun, “Robust hash for detecting and localizing image tampering,” in Proc. IEEE Int. Conf. Image Process. (ICIP), vol. 6.Sep./Oct. 2007, pp. VI-117–VI-120. [3] M. Tagliasacchi, G. Valenzise, and S. Tubaro, “Hash-based identification, of sparse image tampering,” IEEE Trans. Image Process., vol. 18, no. 11,pp. 2491–2504, Nov. 2009. [4] D. Zou, Y. Q. Shi, Z. Ni, and W. Su, “A semi-fragile lossless digital watermarking scheme based on integer wavelet transform,” IEEE Trans. Circuits Syst. Video Technol., vol. 16, no. 10, pp. 1294–1300,Oct. 2006. [5] A. Swaminathan, M. Wu, and K. J. R. Liu, “Digital image forensics via intrinsic fingerprints,” IEEE Trans. Inf. Forensics Security, vol. 3, no. 1,pp. 101–117, Mar. 2008. [6] X. B. Kang and S. M. Wei, “Identifying tampered regions using singular value decomposition in digital image forensics,” in Proc. Int. Conf.Comput. Sci. Softw. Eng., vol. 3. Dec. 2008, pp. 926–930. [7] C. B. Adsumilli, M. C. Q. Farias, S. K. Mitra, and M. Carli, “A robust error concealment technique using data hiding for image and video transmission over lossy channels,” IEEE Trans. Circuits Syst. Video, Technol., vol. 15, no. 11, pp. 1394–1406, Nov. 2005. [15] M. Chen, Y. Zheng, and M. Wu, “Classification–based spatial error concealment for visual communications,” EURASIP J. Appl. Signal, Process., vol. 2006, pp. 1–17, Jan. 2006, Art. ID 13438. [16] G. Gur, Y. Altug, E. Anarim, and F. Alagoz, “Image error concealment using watermarking with subbands for wireless channels,” IEEE Commun. Lett., vol. 11, no. 2, pp. 179–181, Feb. 2007. [17] A. Yilmaz and A. A. Alatan, “Error detection and concealment for video transmission using information hiding,” Signal Process., Image Commun., vol. 23, no. 4, pp. 298–312, 2008.

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