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Hybrid Method for Copy-Move Forgery Detection in Digital Images

  • I. J. Sreelakshmy
  • Binsu C. Kovoor
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 30)

Abstract

Digital image authenticity is significant in many social areas. Image forgery detection becomes a challenging task. Copy-move forgery is one of the tampering techniques which is frequently used, part of the image is copied and pasted to other parts of the same image. This paper proposes a new method for copy-move forgery detection. Proposed method integrates both block-based and keypoint-based forgery detection. Host image is first divided into blocks and keypoints are extracted from each image block. Blocks are compared based on the keypoints in them. Number of similar keypoints identified from a pair of blocks exceeds a preset threshold, then those block pair is matched. Matched blocks are considered as the forged region and Output is displayed after neighbour pixel merging and morphology operations. The accuracy of the method is calculated and analysed with different images.

Keywords

Copy-move forgery Segmentation Keypoints 

References

  1. 1.
    Fridrich AJ, Soukal BD, Lukas AJ (2003) Detection of copy-move forgery in digital images. In: Proceedings of digital forensic research workshopGoogle Scholar
  2. 2.
    Popescu AC, Farid H (2004) Exposing digital forgeries by detecting duplicated image regions. Department Computer Science, Dartmouth College, Technology Report TR2004-515Google Scholar
  3. 3.
    Mahdian B, Saic S (2007) Detection of near-duplicated image regions. Comput Recogn Syst 2:187–195Google Scholar
  4. 4.
    Luo W, Huang J, Qiu G (2006) Robust detection of region-duplication forgery in digital image. In: 18th international conference on pattern recognition, vol 4. IEEE, New YorkGoogle Scholar
  5. 5.
    Cao Y (2012) A robust detection algorithm for copy-move forgery in digital images. Forensic Sci Int 214(1):33–43CrossRefGoogle Scholar
  6. 6.
    Hayat K, Qazi T (2017) Forgery detection in digital images via discrete wavelet and discrete cosine transforms. Comput Electr EngGoogle Scholar
  7. 7.
    Bayram S, Sencar HT, Memon N (2009) An efficient and robust method for detecting copy-move forgery. In: IEEE international conference on acoustics, speech and signal processingGoogle Scholar
  8. 8.
    Huang H, Guo W, Zhang Y (2008) Detection of copy-move forgery in digital images using SIFT algorithm. In: Pacific-Asia workshop on computational intelligence and industrial application, PACIIA’08, vol 2. IEEE, New YorkGoogle Scholar
  9. 9.
    Bo X, Junwen W, Guangjie L, Yuewei D (2009) Image copy-move forgery detection based on SURF. In: Proceedings of IEEE international conference on multimedia information network security (MINES), pp 889–892Google Scholar
  10. 10.
    Ardizzone E, Bruno A, Mazzola G (2015) Copymove forgery detection by matching triangles of keypoints. IEEE Trans Inf Forensics Secur 10(10):2084–2094CrossRefGoogle Scholar
  11. 11.
    Yu L, Han Q, Niu X (2016) Feature point-based copy-move forgery detection: covering the non-textured areas. Multimedia Tools Appl 75(2):1159–1176CrossRefGoogle Scholar
  12. 12.
    Pun C-M, Yuan X-C, Bi X-L (2015) Image forgery detection using adaptive over-segmentation and feature point matching. IEEE Trans Inf Forensics Secur 10(8):1705–1716CrossRefGoogle Scholar
  13. 13.
    Christlein V, Riess C, Jordan J, Riess C, Angelopoulou E (2012) An evaluation of popular copy-move forgery detection approaches. IEEE Trans Inf Forensics Secur 7:1841–1854CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Cochin University of Science and TechnologyKochiIndia

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