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Considerations of Image Compression Scheme Hiding a Part of Coded Data into Own Image Coded Data

  • Conference paper
Signal Processing, Image Processing and Pattern Recognition (SIP 2009)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 61))

Abstract

In this paper, it is considered the image compression scheme, in which a part of coded data extracted in the coding process is hidden into the other parts of coded data of own image, especially into the block address data of the best matching block within restricted blocks. The proposed scheme is able to be used in a fractal image coding in which the best matching domain block is searched, in a vector quantization in image coding in which the best matching vector is searched, and in motion compensation of moving picture in which the best matching motion vector is searched. We study each image coding method and consider the features of each coding method using the proposed scheme.

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References

  1. Iwata, M., Miyake, K., Shiozaki, A.: Digital Watermarking Method to Embed Indes Data into JPEG Images. IEICE, Trans. Fundamentals E85-A(10), 2267–2271 (2002)

    Google Scholar 

  2. Iwata, M., Miyake, K., Shiozaki, A.: Digital Steganography Utilizing Features of JPEG Images. IEICE, Trans. Fundamentals E87-A(4), 929–936 (2004)

    Google Scholar 

  3. Sugimoto, Kawada, R., Koike, A., Matsumoto, S.: Automatic Objective Picture Quality Measurement Method Using Invisible Marker Signal. IEICE Trans. Information and Systems J88-D-II(6), 1012–1023 (2005)

    Google Scholar 

  4. Jacquin, E.: A novel fractal-coding technique for digital images. In: IEEE Int.Conf. on Acoustic, Speech and Signal Processing, M8.2, vol. 4, pp. 2225–2228 (1990)

    Google Scholar 

  5. Beaumont, L.M.: Image data compression of fractal techniques. BT Technology 9(4), 93–109 (1992)

    Google Scholar 

  6. Kim, K., Park, R.H.: Image coding based on fractal approximation and vector quantization. In: IEEE Int. Conf., on Image Processing, vol. 3(13-16), pp. 132–136 (1994)

    Google Scholar 

  7. Linde, Y., Buzo, A., Gray, R.M.: An algorithm for vector quantizer design. IEEE Trans. Commun. COM-28(1), 84–95 (1980)

    Article  Google Scholar 

  8. MPEG Software Simulation Group, MPEG-2 Video Codec, http://www.mpeg.org/MPEG/video/mssg-free-mpeg-software.html

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Author information

Authors and Affiliations

  1. Computing and Fundamental Dep., FPT University, 15B My Dinh, Cau Giay, Hanoi, Vietnam

    Hideo Kuroda

  2. Faculty of Engineering, Nagasaki University, Nagasaki, 852-8521, Japan

    Makoto Fujimura

  3. Graduate School of Science and Technology, Nagasaki University, Nagasaki, 852-8521, Japan

    Kazumasa Hamano

Authors
  1. Hideo Kuroda
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  2. Makoto Fujimura
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  3. Kazumasa Hamano
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Editor information

Editors and Affiliations

  1. University of Warsaw and Infobright Inc., Poland

    Dominik Ślęzak

  2. Indian Statistical Institute, India

    Sankar K. Pal

  3. University of Tasmania, 7001, Hobart, Australia

    Byeong-Ho Kang

  4. Lab. of Multimedia Information Technology (MMIT), East China Normal University (ECNU), P.O. Box, 200062, Shanghai, China

    Junzhong Gu

  5. Nagasaki University, Japan

    Hideo Kuroda

  6. Hannam University, 306-791, Daejeon, South Korea

    Tai-hoon Kim

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© 2009 Springer-Verlag Berlin Heidelberg

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Kuroda, H., Fujimura, M., Hamano, K. (2009). Considerations of Image Compression Scheme Hiding a Part of Coded Data into Own Image Coded Data. In: Ślęzak, D., Pal, S.K., Kang, BH., Gu, J., Kuroda, H., Kim, Th. (eds) Signal Processing, Image Processing and Pattern Recognition. SIP 2009. Communications in Computer and Information Science, vol 61. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10546-3_37

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  • DOI: https://doi.org/10.1007/978-3-642-10546-3_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10545-6

  • Online ISBN: 978-3-642-10546-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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