Abstract
Copy-move forgery is one of the types of image manipulation which is widely used due to simplicity and effectiveness. In this method, part of the original image is copied and pasted to the desired location in the same image. The goal of detecting copy-move forgery is to find areas of the image that are identical or very similar. One of the important issues that some of the earlier algorithms suffer from is that the forged area is rotated or resized after attachment. In this research, a new approach is presented to detect copy-move forgery in digital images based on discrete wavelet decomposition along with multiple features extracted by Gabor filter to improve the function of detecting similar areas of the image. Experiments have shown that this algorithm recognizes similar areas with relatively good accuracy and is resistant to rotation and change in the scale of the forged area.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Birajdar GK, Mankar VH (2013) Digital image forgery detection using passive techniques: a survey. Digit Invest: 226–245
Chauhan A (2015) Digital watermarking-revisit. J Comput Sci Inf Technol 6(1):833–838
Diane N, Xingming WNS, Moise FK (2014) A survey of partition-based techniques for copy-move forgery detection. Sci World J 1–13
Myna AN, Venkateshmurthy MG, Patil C (2007) Detection of region duplication forgery in digital images using wavelets and log-polar mapping. In: International conference on computing intelligence multimedia application, pp 371–377
Li G, Wu Q, Tu D, Sun S (2007) A sorted neighborhood approach for detecting duplicated regions in image forgeries based on DWT and SVD. In: IEEE international conference on multimedia and expo, pp 1750–1753
Khan S, Kulkarni A, Khan ES, Kulkarni EA (2010) An efficient method for detection of copy-move forgery using discrete wavelet transform. Int J Comput Sci Eng: 1810
Gan Y, Zhong J (2015) Image copy-move forgery blind detection algorithm based on the normalized histogram multi-feature vectors. J Softw Eng: 254–264
Luo W, Huang J, Qiu G (2006) Robust detection of region-duplication forgery in digital image. In: 18th international conference pattern recognition, pp 18–21
Ryu SJ, Lee MJ, Lee HK (2010) Detection of copy-rotate-move forgery using zernike moments. Lecture notes computing science (including Subseries. Lecture notes artificial intelligence lecture notes bioinformatics), pp 51–65
Bayram S, Sencar HT, Memon N (2009) An efficient and robust method for detecting copy-move forgery. In: IEEE international conference on acoustics speech signal process. ICASSP 2009. IEEE, pp 1053–1056
AndaJan L, Fridrich J, Soukal D (2008) Detection of copy-move forgery in digital images using sift algorithm. In: Proceedings—2008 Pacific-Asia workshop on computational intelligence and industrial application, PACIIA, pp 272–276
Popescu AC, Farid H (2004) Exposing digital forgeries by detecting duplicated image regions. Department Computing Science, Dartmouth College. Technical Report. TR2004-515, no. 2000, pp 1–11, 2004
Davarzani R, Yaghmaie K, Mozaffari S, Tapak M (2013) Copy-move forgery detection using multiresolution local binary patterns. Forensic Sci Int: 61–72
Gabor D (1946) Theory of communication. Part 1: the analysis of information. J Inst Electr Eng III Radio Commun Eng: 429–441
Daugman JG (1985) Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. J Opt Soc Am A:1160
Seryasat OR, Haddadnia J, Ghayoumi-Zadeh H (2015) A new method to classify breast cancer tumors and their fractionation. Ciência e Nat 37:51–57
Haghighat M, Zonouz S, Abdel-Mottaleb M (2013) Identification using encrypted biometrics. In: Computer analysis of images and patterns, pp 440–448
Kang X, Li Y, Qu Z, Huang J (2012) Enhancing source camera identification performance with a camera reference phase sensor pattern noise. IEEE Trans Inf Forensics Secur: 393–402
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Mokhtari Ardakan, M., Yerokh, M., Akhavan Saffar, M. (2019). A New Method to Copy-Move Forgery Detection in Digital Images Using Gabor Filter. In: Montaser Kouhsari, S. (eds) Fundamental Research in Electrical Engineering. Lecture Notes in Electrical Engineering, vol 480. Springer, Singapore. https://doi.org/10.1007/978-981-10-8672-4_9
Download citation
DOI: https://doi.org/10.1007/978-981-10-8672-4_9
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-8671-7
Online ISBN: 978-981-10-8672-4
eBook Packages: EngineeringEngineering (R0)