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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Fridrich AJ, Soukal BD, Lukas AJ (2003) Detection of copy-move forgery in digital images. In: Proceedings of digital forensic research workshop
Popescu AC, Farid H (2004) Exposing digital forgeries by detecting duplicated image regions. Department Computer Science, Dartmouth College, Technology Report TR2004-515
Mahdian B, Saic S (2007) Detection of near-duplicated image regions. Comput Recogn Syst 2:187–195
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 York
Cao Y (2012) A robust detection algorithm for copy-move forgery in digital images. Forensic Sci Int 214(1):33–43
Hayat K, Qazi T (2017) Forgery detection in digital images via discrete wavelet and discrete cosine transforms. Comput Electr Eng
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 processing
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 York
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 889–892
Ardizzone E, Bruno A, Mazzola G (2015) Copymove forgery detection by matching triangles of keypoints. IEEE Trans Inf Forensics Secur 10(10):2084–2094
Yu L, Han Q, Niu X (2016) Feature point-based copy-move forgery detection: covering the non-textured areas. Multimedia Tools Appl 75(2):1159–1176
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):1705–1716
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 7:1841–1854
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Sreelakshmy, I.J., Kovoor, B.C. (2019). Hybrid Method for Copy-Move Forgery Detection in Digital Images. In: Pandian, D., Fernando, X., Baig, Z., Shi, F. (eds) Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB). ISMAC 2018. Lecture Notes in Computational Vision and Biomechanics, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-00665-5_13
Download citation
DOI: https://doi.org/10.1007/978-3-030-00665-5_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-00664-8
Online ISBN: 978-3-030-00665-5
eBook Packages: EngineeringEngineering (R0)