Skip to main content

An Algorithm for Asymmetric Clipping Detection Based on Parameter Optimization

  • Conference paper
  • First Online:
  • 1149 Accesses

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 82))

Abstract

Asymmetric clipping of digital images is a common method of image tampering, and the existing identification techniques of which are relatively meager. Camera calibration technology is an important method to determine the tampering of asymmetric cutting, but the proposed algorithm has made too many assumptions on the internal parameters matrix of the camera, resulting in some error. This paper presents a parameter optimization algorithm based on camera calibration: by keeping the four parameters in the original camera’s five internal parameters, after approximate processing, to achieve that a single picture contains no coplanar of the two regular geometric figures can calculate the coordinates of the principal point, and as a basis for the image forensics of the asymmetric cutting tampering. The experimental results show that the proposed algorithm can effectively estimate the camera parameters, the application scope and accuracy can be improved greatly, and can accurately detect the image tampering behavior of asymmetric clipping.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Bharati, A., Singh, R.: Detecting facial retouching using supervised deep learning. IEEE Trans. Inf. Forensics Secur. 11(9), 1903–1913 (2016)

    Article  Google Scholar 

  2. Ke, Y., Shan, Q., Qin, F., Min, W.: Image recapture detection using multiple features. Int. J. Multimedia Ubiquit. Comput. 8(5), 71–82 (2013)

    Article  Google Scholar 

  3. Ardizzone, E., Bruno, A., Mazzola, G.: Copy-move forgery detection by matching triangles of key points. IEEE Trans. Inf. Forensics Secur. 10(10), 2084–2094 (2015)

    Article  Google Scholar 

  4. El-Alfy, E.S.M., Qureshi, M.A.: Combining spatial and DCT based Markov features for enhanced blind detection of image splicing. Formal Pattern Anal. Appl. 18(3), 1–11 (2014)

    MathSciNet  Google Scholar 

  5. Meng, X., Niu, S.: Technology of digital image tampering based on double JPEG compression. In: National Conference on Information Hiding and Multimedia Information Security (2010)

    Google Scholar 

  6. Guo, C., Hong, Y.: Automatic camera calibration method using checkerboard target. J. Comput. Eng. Appl. 52(12), 176–179 (2016)

    Google Scholar 

  7. Zhang, Y., Win, L.L., Goh, J., Thing, V.L.L.: image region forgery detection: a deep learning approach. In: Proceedings of the Singapore Cyber-Security Conference (SG-CRC) (2016)

    Google Scholar 

  8. Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)

    Article  Google Scholar 

  9. Meng, X., Niu, S.: Asymmetric crop detection algorithm based on camera calibration. J. Electron. Inf. Technol. 34(10) (2012)

    Google Scholar 

  10. Johnson, M., Farid, H.: Detecting photographic composites of people. In: 6th International Workshop on Digital Watermarking, Guangzhou, China, vol. 5041, pp. 19–33 (2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Jiwei Zhang , Shaozhang Niu , Yueying Li or Yuhan Liu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Zhang, J., Niu, S., Li, Y., Liu, Y. (2018). An Algorithm for Asymmetric Clipping Detection Based on Parameter Optimization. In: Pan, JS., Tsai, PW., Watada, J., Jain, L. (eds) Advances in Intelligent Information Hiding and Multimedia Signal Processing. IIH-MSP 2017. Smart Innovation, Systems and Technologies, vol 82. Springer, Cham. https://doi.org/10.1007/978-3-319-63859-1_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-63859-1_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63858-4

  • Online ISBN: 978-3-319-63859-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics