Abstract
The main concern of steganography (image hiding) methods is to embed a secret image into a host image in such a way that it causes minimum distortion to the host; to make it possible to extract a version of secret image from the host in such a way that the extracted version of secret image be as similar as possible to its original version (this should be possible even after usual attacks on the host image), and to provide ways of embedding secret images with larger size into a given host image. In this paper we propose a method that covers all above mentioned concerns by suggesting the idea of finding from an image data base, the most suitable host for a given secret image. In our method, the secret and host images are divided into blocks of size 4 ×4. Each block in secret image is taken as a texture pattern for which using Gabor filter, the most similar block is found among the blocks of host image candidates. Using this similarity criterion and Kohonen neural network, the most suitable host image is selected from an image database. Embedding is done by placing the blocks of secret image on their corresponding blocks in the selected host image. The location addresses of blocks in host that were replaced by blocks of secret image are saved. They are converted to a bit string that is embedded in DCT coefficients of the hybrid image. Our experimental results showed a high level of capacity, robustness and minimum distortion when using standard images as secret and host images.
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References
Tsai, P., Hu, Y.C., Chang, C.C.: An image hiding technique using block truncation coding. In: Proceedings of Pasific Rim Workshop on Digital Steganography, July 2002, Kitakyushu, Japan, pp. 54–64 (2002)
Wang, R.Z., Lin, J.F., Lin, J.C.: Image hiding by optimal LSB substitution and genetic algorithm. Journal of Pattern Recognition 34(3), 671–683 (2001)
Chae, J.J., Mukherjee, D., Manjunath, B.S.: Color Image Embedding using Multi-dimensional Lattice Structures. In: Proceeding of IEEE International Conference of Image Processing (ICIP 1998), October, 1998, Chicago, vol. 1, pp. 460–464 (1998)
Kim, Y.S.: A wavelet based watermarking method for digital images using human visual system. Sogang University (1999)
Chang, C.C., Chen, L.Z., Chung, L.Z.: A steganograhpic method based upon JPEG and quantization table modification. Information Society 141, 123–138 (2002)
Spaukling, J., Hoda, H., Shirazi, M.N., Kawaguchi, E.: BPCS steganography using EZW lossy compression images. Pattern Recognition Letters 23, 1579–1587 (2002)
Tsai, P., Hu, Y.C., Chang, C.C.: A progressive secret reveal system based on SPIHT image transmission. Journal of Signal Processing: Image Communication 19, 285–297 (2004)
Marvel, L.M.: Image steganography for hidden communication. University of Delaware, Spring (1999)
Ma, W.Y.: Texture features and learning similarity. University of California, Santa Barbara (1996)
Manjunath, B.S.: Gabor wavelet transform and application to problems in early vision. In: Proc.26th conference on signals, systems and computers, October 1992, Pacific Grove, CA, pp. 796–800 (1992)
Principe, J.C., Euliano, N.R., Lefebvre, W.C.: Neural and Adaptive Systems: Fundamentals Through Simulations. John Wiley and Sons, Chichester (2000)
Zahedi Kermani, Z., Jamzad, M.: A robust steganography algorithm based on texture similarity using Gabor filter. In: The 5th IEEE Int. Symposium Signal Processing and Information Technology (ISSPIT), December 18-21, 2005, Athens, Greece (2005)
Csurka, C., Deguillaume, F., Ruanaidh, J.J.K.O., Pun, T.: A Bayesian, approach to affine transformation resistant image and video watermarking. In: Proc. Int. Workshop on Information Hiding, September 1999, Dresden, Germany (1999)
Piva, A., Barni, M., Bartonili, F., Cappellini, V.: DCT-based watermark recovering without resorting to the un- uncorrupted original image. In: IEEE Int. Conference on Image Processing, October 1997, Santa Barbara, CA, vol. 1, pp. 520–523 (1997)
Franco, R., Malah, D.: Adaptive Image Partitioning for Fractal Coding Achieving Designated Rates Under a Complexity Constraint. In: IEEE 2001 International Conference on Image Processing (2001)
Lyu, S., Farid, H.: Detecting hidden messages using higher-order statistics and support vector machines. In: Proc. 5th Int. Workshop on Information Hiding (2002)
Lyu, S., Farid, H.: Steganalysis using color wavelet statistics and one-class support vector machines. In: Proc. SPIE 5306, pp. 35–45 (2004)
Lyu, S., Farid, H.: Steganalysis using higher order image statistics. IEEE Trans. Inf. Forens. Secur. 111–119 (2006)
Kharrazi, M., Husrev, T., Sencar, H.T., Memon, N.: ’Performance study of common image steganography and steganalysis techniques’. Journal of Electronic Imaging 15(4), 41–104 (2006)
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Jamzad, M., Kermani, Z.Z. (2008). Secure Steganography Using Gabor Filter and Neural Networks. In: Shi, Y.Q. (eds) Transactions on Data Hiding and Multimedia Security III. Lecture Notes in Computer Science, vol 4920. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69019-1_3
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DOI: https://doi.org/10.1007/978-3-540-69019-1_3
Publisher Name: Springer, Berlin, Heidelberg
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