ICTACT Journal on Image and Video Processing

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Hiding Text in Digital Images Using Permutation Ordering and Compact Key Based Dictionary


Affiliations
1 Department of Statistics, Manonmaniam Sundaranar University, India
2 Department of Computer Science and Engineering, MET’s School of Engineering, India
     

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Digital image steganography is an emerging technique in secure communication for the modern connected world. It protects the content of the message without arousing suspicion in a passive observer. A novel steganography method is presented to hide text in digital images. A compact dictionary is designed to efficiently communicate all types of secret messages. The sorting order of pixels in image blocks are chosen as the carrier of embedded information. The high correlation in image pixel values means reordering within image blocks do not cause high distortion. The image is divided into blocks and perturbed to create non repeating sequences of intensity values. These values are then sorted according to the message. At the receiver end, the message is read from the sorting order of the pixels in image blocks. Only those image blocks with standard deviation lesser than a given threshold are chosen for embedding to alleviate visual distortion. Information Security is provided by shuffling the dictionary according to a shared key. Experimental Results and Analysis show that the method is capable of hiding text with more than 4000 words in a 512×512 grayscale image with a peak signal to noise ratio above 40 decibels.

Keywords

Digital Images, Steganography, Permutation Ordering, Lehmer Codes, Text Hiding.
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  • K. Sayood, “Introduction to Data Compression”, Available at:http://rahilshaikh.weebly.com/uploads/1/1/6/3/11635894/data_compression.pdf.

  • Kamrul Hasan Talukderi and Koichi Harada, “Haar Wavelet Based Approach for Image Compression and Quality Assessment of Compressed Image”, International Journal of Applied Mathematics, Vol. 36, pp. 1-9, 2007.

  • Peter Wayner, “Compression Algorithm for Real Programmer”, 1st Edition, Elsevier, 1999.

  • Markus Kuhn, “Digital Signal Processing”, Available at: https://www.cl.cam.ac.uk/teaching/0809/DSP/.

  • Ken Cabeen and Peter Gent, “Image Compression and the Discrete Cosine Transform”, Available at: https://www.math.cuhk.edu.hk/~lmlui/dct.pdf.

  • Sean Dunn, Available at: http://davis.wpi.edu/~matt/courses/color

  • Colm Mulcahy, “Image Compression using the HAAR Wavelet Transform”, Spelman Science and Math Journal, pp. 22-31, 1997.

  • Ryuji Matsuoka, Mitsuo Sone, Kiyonari Fukue, Kohei Cho and Haruhisa Shimoda, “Quantitative Analysis of Image Quality of Lossy Compression Images”, Available at: https://pdfs.semanticscholar.org/e929/fe4e037d80a226549054fd35bced632e2009.pdf.

  • James Z. Wang, “Wavelets and Imaging Informatics: A Review of the Literature”, Journal of Biomedical Informatics, Vol. 34, No. 2, pp. 129-141, 2001.

  • Yves Meyer, “Wavelets Algorithms and Applications”, SIAM Journal on Applied Mathematics, Vol. 53, No. 1, pp. 1-6, 1993.

  • Charles K. Chui, “An Introduction to Wavelets”, Academic Press, 1992.

  • C.K. Chui, “Wavelets: A Tutorial in Theory and Applications”, Academic Press, 1992.

  • Subhasis Saha, “Image Compression - from DCT to Wavelets: A Review”, Crossroads, Vol. 6, No. 3, pp. 12-21, 2000.

  • Li Wern Chew, Li-Minn Ang and Kah Phooi Seng, “Survey of Image Compression Algorithms in Wireless Sensor Networks”, Proceedings of International Symposium on Information Technology, pp. 1-9, 2008.

  • D. Cruz, T. Ebrahimi, J. Askelof, M. Larsson and C. Christopoulos, “Coding of Still Picture”, Proceedings of 45th SPIE Applications of Digital Image Processing, Vol. 4115, pp. 1-10, 2000.

  • Suchitra Shrestha and Khan Wahid, Hybrid DWT-DCT Algorithm for Biomedical Image and Video Compression Applications, Proceedings of 10th IEEE International Conference on Information Sciences, Signal Processing and their Applications, pp. 280-283, 2010.

  • Swapna Subudhiray and Abhishek Kr. Srivastav, “Implementation of Hybrid Dwt-Dct Algorithm For Image Compression: A Review”, International Journal of Research in Engineering and Applied Sciences, Vol. 2, No. 2, pp. 1200-1210, 2012.

  • M. Shwetha, P. Ashwini and B.M. Sujatha, “Analysis of Image Compression Algorithms in WSN: A Review”, International Journal of Science, Engineering and Technology Research, Vol. 3, No. 4, pp.1029-1032, 2014.

  • Sonja Grgic, Kresimir Kers and Mislav Grgic, “Image Compression using Wavelets”, Proceedings of IEEE International Symposium on Industrial Electronics, pp. 99-104, 1999.

  • R.Sudhakar, R Karthiga and S. Jayaraman, “Image Compression using Coding of Wavelet Coefficients-A Survey”, ICGST-GVIP Journal, Vol. 5, No. 6, pp. 25-38, 2005.

  • Renu Sharma and Matish Garg, “Comparative analysis of JPEG DCT, Haar and Daubechies Wavelet, Fractal for Image Compression”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 4, No. 1, pp. 1227-1234, 2014.

  • S. Sridhar, P. Rajesh Kumar and K.V. Ramanaiah, “Wavelet Transform Techniques for Image Compression-An Evaluation”, International Journal of Image, Graphics and Signal Processing, Vol. 2, pp. 54-67, 2014.

  • USC-SIPI Image Database, Available at: http://sipi.usc.edu/database/database.php?volume=misc, Accessed on 2014.


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  • Hiding Text in Digital Images Using Permutation Ordering and Compact Key Based Dictionary

Abstract Views: 225  |  PDF Views: 2

Authors

Nagalinga Rajan
Department of Statistics, Manonmaniam Sundaranar University, India
R. Sunder
Department of Computer Science and Engineering, MET’s School of Engineering, India

Abstract


Digital image steganography is an emerging technique in secure communication for the modern connected world. It protects the content of the message without arousing suspicion in a passive observer. A novel steganography method is presented to hide text in digital images. A compact dictionary is designed to efficiently communicate all types of secret messages. The sorting order of pixels in image blocks are chosen as the carrier of embedded information. The high correlation in image pixel values means reordering within image blocks do not cause high distortion. The image is divided into blocks and perturbed to create non repeating sequences of intensity values. These values are then sorted according to the message. At the receiver end, the message is read from the sorting order of the pixels in image blocks. Only those image blocks with standard deviation lesser than a given threshold are chosen for embedding to alleviate visual distortion. Information Security is provided by shuffling the dictionary according to a shared key. Experimental Results and Analysis show that the method is capable of hiding text with more than 4000 words in a 512×512 grayscale image with a peak signal to noise ratio above 40 decibels.

Keywords


Digital Images, Steganography, Permutation Ordering, Lehmer Codes, Text Hiding.

References