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A Perfect Hash Model Used for Image Content Tamper Detection

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Book cover Advances in Image and Graphics Technologies (IGTA 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 634))

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Abstract

An effective image content temper detection scheme that uses perfect hash model is proposed in this paper. Aiming at low detection failing rates and high detection successful rates in image tamper localization, the proposed scheme uses perfect hash model to overcome easy collisions of the random numbers to enhance the effectiveness in authentication procedure. This scheme embeds perfect hash information in the LSBs of the original image to protect image content. The experimental results demonstrate that the proposed scheme has a good performance and can be used for image authentication applications.

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Author information

Authors and Affiliations

  1. NARI Technology Development Co., Ltd., Anhui NARI Zenith Electricity & Electronic Co., Ltd., Hefei, 230088, China

    Jing Sun

  2. Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Computer Science and Technology, Anhui University, Hefei, 230039, China

    Wan-Li Lyu

Authors
  1. Jing Sun
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  2. Wan-Li Lyu
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Corresponding author

Correspondence to Wan-Li Lyu .

Editor information

Editors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Tieniu Tan

  2. Peking University, Beijing, China

    Guoping Wang

  3. Tsinghua University, Beijing, China

    Shengjin Wang

  4. Beijing Institute of Technology, Beijing, China

    Yue Liu

  5. Peking University, Beijing, China

    Xiaoru Yuan

  6. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Ran He

  7. Peking University, Beijing, China

    Sheng Li

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© 2016 Springer Science+Business Media Singapore

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Sun, J., Lyu, WL. (2016). A Perfect Hash Model Used for Image Content Tamper Detection. In: Tan, T., et al. Advances in Image and Graphics Technologies. IGTA 2016. Communications in Computer and Information Science, vol 634. Springer, Singapore. https://doi.org/10.1007/978-981-10-2260-9_25

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  • DOI: https://doi.org/10.1007/978-981-10-2260-9_25

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2259-3

  • Online ISBN: 978-981-10-2260-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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