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A Novel Image Hiding Scheme Based on VQ and Hamming Distance

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Data hiding is popularly employed in protecting the copyright, secret information and communication secretly with the convenience of network communication. In order to reduce the amount the transmitted data via network, VQ (vector quantization) is applied to compressing the transmitted data. Since VQ is a low-bit-rate compression scheme, it is difficult to find large redundant hiding space and to get stego-images with high quality for hiding data in VQ-based compressed images. A hiding method for VQ-based compressed images is proposed in this paper according to the Hamming distance between the index values of codewords. Our method makes hiding data more effective and provides stego-images with higher quality than other conventional methods. Experimental results demonstrate the effectiveness and the feasibility of our method.
Słowa kluczowe
Wydawca
Rocznik
Strony
217--228
Opis fizyczny
bibliogr. 12 poz., fot., tab.
Twórcy
autor
autor
autor
  • Department of Computer Science and Information Management, Providence University, Taichung 433, Tiwan, R.O.C., ccc@cs.ccu.edu.tw
Bibliografia
  • [1] W. Bender, D. Gruhl, N. Morimoto, and A. Lu: Techniques for Data Hiding, IBM Systems Journal, 35 (3, 4) (1996) 313-336.
  • [2] N. Bourbakits and C. Alexopoulos: Picture Data Encryption Using Scan Patterns, Pattern Recognition, 25 (6) (1992) 567-581.
  • [3] W. H. Equitz: A New Vector Quantization Clustering Algorithm, IEEE Transactions on Acoustics, Speech, and Signal Processing, 37 (10) (1989) 1568-1575.
  • [4] R. M. Gray: Vector Quantization, IEEE Acoustics, Speech and Signal Processing Magazine, 1 (1984) 4-29.
  • [5] J. K. Jan and Y. M. Tseng: On the Security of Image Encryption Method, Information Processing Letters, 60 (1996) 261-265.
  • [6] Y. K. Lee and L. H. Chen: High Capacity Steganographic Model, IEE Proceedings-Vision, Image and Signal Processing, 147 (3) (2000) 288-294.
  • [7] W. N. Lie and L. C. Chang: Data Hiding in Images with Adaptive Numbers of Least Significant Bits Based on the Human Visual System, Proceedings of 1999 the International Conference on Image Processing, Kobe, Japan, 1, 1999, pp. 286-290.
  • [8] Y. C. Lin and C. C. Wang: Digital Images Watermarking by Vector Quantization, Proceedings of the 9th National Computer Symposium, Taichung, Taiwan, 1999, pp. 76-87.
  • [9] Y. Linde., A. Buzo, and R. M. Gray: An Algorithm for Vector Quantizer Design, IEEE Transactions on Communications, 28 (1980) 4-95.
  • [10] T. Ogihara, D. Nakamura, and N. Yokoya: Data Embedding into Pictorial Images with Less Distortion using Discrete Cosine Transform, Proceedings of the 13th IAPR International Conference on Pattern Recognition (13ICPR), Vienna, Austria, 1996, pp. 675-679.
  • [11] R. L. Rivest, A. Shamir, and L. Adleman: A Method for Obtaining Digital Signatures and Public-Key Cryptosystems, Communications of the Association for Computing Machinery, 21 (2) (1978) 120-126.
  • [12] J. Zhou, Y. Shoham, and A. Akansu: Simple Fast Vector Quantization of the Line Spectral Frequencies, Proceedings of the 4th International Conference on Spoken Language Processing, Philadelphia, 2, 1996, pp. 945-948.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS5-0010-0008
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