Skip to main content

An Efficient Block Phase Correlation Approach for CMFD System

  • Conference paper
  • First Online:
Progress in Computing, Analytics and Networking

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 710))

Abstract

Copy–move forgery is the most basic technique to alter an image. In this method, one region of an image is copied and pasted into another location of the same image, with an attempt to cover a potentially important feature or duplicate some features. As the copied part resides in the same image, its important properties, such as noise, brightness, texture, are compatible with rest of the image making its detection very difficult. The existing techniques for detecting copy–move forgery suffer from the computational time problem. In this paper, an efficient block-based copy–move forgery detection algorithm is present that reduces the processing time in identifying the duplicated regions in an image. Proposed method is tested on CoMoFoD dataset. Experimental results show the ability of the proposed method to accurately detect the tampered regions as well as reducing the time complexity.

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

Access this chapter

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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Popescu, A. C., and Farid, H.: ‘Exposing digital forgeries by detecting traces of resampling’, IEEE Transactions on Signal Processing, 2005, 53, (2), pp. 758–767.

    Google Scholar 

  2. Ting, Z., and Rang-Ding, W. : ‘Copy-move forgery detection based on SVD in digital image’. Proceedings in International Congress on Image and Signal Processing (CISP), October 2009, pp. 1–5.

    Google Scholar 

  3. Fridrich, J., Soukal, D., and Lukas, J.: ‘Detection of copy-move forgery in digital images’. Proceedings of Digital Forensic Research Workshop, 2003.

    Google Scholar 

  4. Sunil Kumar, Jagannath Desai, Shaktidev Mukherjee, “A Fast DCT Based Method for Copy Move Forgery Detection”, Proceeding of the 2013 IEEE Second International Conference of Image Information Processing (ICIIP-2013).

    Google Scholar 

  5. Cao, Y. Gao, T. Fan, L. Yang, Q. (2012), “A Robust Detection Algorithm For Copy-Move Forgery in Digital Images”, Forensic Science International, vol. 214, No. 13, pp. 33–43.

    Google Scholar 

  6. Elhem Mohebbian, Mahdi Hariri, “Increase the efficiency of DCT method for detection of Copy-Move Forgery in complex and smooth images”, International Conference on Knowledge Based Engineering & Innovation(KBEI) Nov 5–6, 2015.

    Google Scholar 

  7. J. Zhang, Z. Feng and Y. Su, A new approach for detecting copy-move forgery in digital images, 11th IEEE Singapore International Conference on the Communication Systems, ICCS, 2008.

    Google Scholar 

  8. Muhammad, G., Hussain, M., Khawaji, K., and Bebis, G.: ‘Blind copy-move image forgery detection using dyadic undecimated wavelet transform’. Proceedings of the international conference on Digital Signal Processing (DSP), July 2011.

    Google Scholar 

  9. D. G. Lowe, Distinctive image features from scale-invariant keypoints, International Journal of Computer Vision, vol. 60, no. 2, pp. 91–110, 2004.

    Google Scholar 

  10. Amerini, I., Ballan, L., Caldelli, R., Bimbo, A.D., and Serra, G.: “A SIFT-based forensic method for copymove attack detection and transformation recovery”, IEEE Transactions on Information Forensics and Security, 2011, 6, (3), pp. 1099–1110.

    Google Scholar 

  11. Xu Bo, Wang Junwen, Liu Guangjie and Dai Yuewei, “Image Copy-move Forgery Detection Based on SURF”, 2010 International Conference on Multimedia Information Networking and Security.

    Google Scholar 

  12. Hsu, H. and Wang, M. (2012), “Detection of Copy-Move Forgery Image Using Gabor Descriptor”, in Proceedings of the International Conference on Anti-Counterfeiting, Security and Identification (ASID 12), IEEE, August 2012, pp. 1–4.

    Google Scholar 

  13. Tralic D., Zupancic I., Grgic S., Grgic M., “CoMoFoD—New Database for Copy-Move Forgery Detection”, in Proc. 55th International Symposium ELMAR-2013, pp. 49–54, September 2013.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Badal Soni .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Soni, B., Das, P.K., Thounaojam, D.M. (2018). An Efficient Block Phase Correlation Approach for CMFD System. In: Pattnaik, P., Rautaray, S., Das, H., Nayak, J. (eds) Progress in Computing, Analytics and Networking. Advances in Intelligent Systems and Computing, vol 710. Springer, Singapore. https://doi.org/10.1007/978-981-10-7871-2_5

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-7871-2_5

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7870-5

  • Online ISBN: 978-981-10-7871-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics