1. Vishnu Vardhan Reddy Mukku Mav ID : 1000989621 Email : vishnu.vardhanreddymukku@mavs.uta.eduvishnu.vardhanreddymukku@mavs.uta.edu Under the guidance of Dr. K. R. Rao

2. RDO -- Rate Distortion Optimization DCT -- Discrete Cosine Transform LSB -- Least Significant Bit HM -- Histogram Manipulation

3. Introduction H.264 compression basics Data representation schemes a)Bit plane replacement b)Spread spectrum c)Histogram manipulation d)Mapping rules e)Divisibility f)Matrix encoding Conclusions References

4. Information hiding refers to the process of inserting information into a host to serve specific purpose(s) [1]. Information hiding is also referred as data embedding. In video domain, the application of information hiding can be coarsely categorized as watermarking, steganography, error recovery (resilient), and general data embedding. Fig. 1. General framework of information hiding [1]

5. Introduction (Cont.) Need for Information hiding for the videos includes, 1) tracking illegal distribution of copyrighted video to secure business revenue. 2) hyperlinking related contents while ensuring the hyperlink information always stays intact with the video to enhance user experiences. 3)monitoring video broadcasts and Internet distributions to generate reports regarding when, where, and how many times a video has been streamed. Fig. 2. Original video (left) and visible watermarked video (right) [1]

6. H.264 encoder: Fig.3: H.264 hybrid video encoder [1]

7. An information hiding method can be illustrated by the relationship among state, entity, and the meaning of each state. Fig.4: State of the entity and its meaning for information hiding [1]

8. Fig.5: Classification of data representation schemes for information hiding in H.264 compressed video [1]

9. Bit plane replacement is widely referred to as least significant bit (LSB), which manipulates the right most bit of an entity. the LSB scheme is the most straightforward way to encode information, with insignificant perceptual quality degradation when applied on the raw pixel values. However, a direct LSB scheme is irreversible.

10. It is widely utilized for watermarking purposes. These techniques can be formulated as [4] w i ∈ {0,1} is the information; v i, v i ’ are the input and output values, ‘a’ is scaling factor. Equation (1) is invertible, Equation (2), (3) are invertible only if v i ≠0.

11. It is applicable to both the spatial and frequency domains. It is a common way to achieve reversible information hiding. However, it requires expensive preprocessing (e.g., vacating a bin for data embedding) and suffers from the under/overflow problems. Fig. 6. Hiding information using histogram [1]

12. Mapping rules rely on a set of codewords for information embedding and extraction purposes. Basically codewords are associated with predefined meaning (e.g., “00,” “01,” “10,” or “11”) and they are chosen based on the information to be embedded. Fig. 7. Mapping rules for macroblock size to embed information [1]

13. The divisibility of a value by a specific divisor can be exploited as an essential property for reversible information hiding. For example, the magnitude of each coefficient in the macroblock is scaled by a prime number when “1” is to be embedded, or leave them as they are (i.e., no change) to embed “0”. A more sophisticated method considers a pair of neighboring pixels x and y, and the value n. These values are then transformed to obey a simple equation as Y i +n X i+1 ≡0 mod (n+1). Where ‘n’ is an integer.

14. In this presentation the Commonly considered data representation schemes and the hiding venues were summarized. In the further steps are the implementation of the information hiding(water marking) using intra mode prediction and block size.

15. [1] Y.Tew and K.Wong, “An Overview of Information Hiding in H.264/AVC Compressed Video,” IEEE Trans. Circuits Syst. Video Technol., vol. 24, NO. 2, pp. 305-319, Feb 2014. [2] J. Mielikainen, “LSB matching revisited,” IEEE Signal Process. Lett., vol. 13, no. 5, pp. 285–287, May 2006. [3] X.Li, B.Yang et al., “A generalization of LSB matching,” IEEE Signal Process. Lett., vol. 16, no. 2, pp. 69–72, Feb.2009. [4]I. J. Cox, J. Kilian, et al. Shamoon, “Secure spread spectrum watermarking for multimedia,” IEEE Trans. Image Process., vol. 6, no. 12, pp. 1673–1687, Dec. 1997. [5] Z. Ni, Y.-Q. Shi, N. Ansari, and W. Su, “Reversible data hiding,” IEEE Trans. Circuits Syst. Video Technol., vol. 16, no. 3, pp. 354–362, Mar.2006. [6] S. Kapotas, E. Varsaki, and A. Skodras, “Data hiding in H.264 encoded video sequences,” in Proc. IEEE 9th Workshop Multimedia Signal Process., pp. 373–376, Oct. 2007.

16. [7] D. Coltuc and J.-M. Chassery, “High capacity reversible watermarking,” in Proc. IEEE Int. Conf. Image Process., pp. 2565–2568 Oct. 2006. [8] J. Fridrich, M. Goljan, and R. Du, “Invertible authentication watermark for JPEG images,” in Proc. Int. Conf. Inform. Technol. Coding Comput., pp. 223–227, Apr. 2001. [9] R. Crandall. (1998, Dec.) Some notes on steganography [Online]. Available: http://www.di.unisa.it/%7eads/corso-security/www/CORSO- 0203/steganografia/LINKS%20LOCALI/matrix-encoding.pdf [10] T. Shanableh, “Matrix encoding for data hiding using multilayer video coding and transcoding solutions,” Signal Process. Image Commun., vol. 27, pp. 1025–1034, Oct. 2012. References (Cont.)