Abstract
This paper proposes an effective image forgery detection scheme that identifies a tampered foreground or background image using image watermarking and alpha mattes. In the proposed method, component-hue-difference-based spectral matting is used to obtain the foreground and background images based on the obtained alpha matte. Next, image watermarking based on the discrete wavelet transform, discrete cosine transform, and singular value decomposition is used to embed two different watermarks into the foreground and background images, respectively. Finally, the difference between the obtained singular values is used to detect tampering of foreground or background image. Experimental results show that the proposed method performs well in terms of image forgery detection.
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References
Bianchi T, Piva A (2012) Image forgery localization via block-grained analysis of JPEG artifacts. IEEE Trans Inf Forensic Secur 7(3):1003–1017
Chang I-C, Yu JC, Chang C-C (2013) A forgery detection algorithm for exemplar-based inpainting images using multi-region relation. Image Vis Comput 31(1):57–71
Christlein V, Riess C, Jordan J, Riess C, Angelopoulou E (2012) An evaluation of popular copy-move forgery detection approaches. IEEE Trans Inf Forensic Secur 7(6):1841–1854
Comaniciu D, Meer P (2002) Mean shift: a robust approach toward feature space analysis. IEEE Trans Pattern Anal Mach Intell 24(5):603–619
Criminisi A, Perez P, Toyama K (2004) Region filling and object removal by exemplar-based image inpainting. IEEE Trans Image Process 13(9):1200–1212
Guan Y, Chen W, Liang X, Ding Z, Peng Q (2008) Easy matting: a stroke based approach for continuous image matting. Comput Graph Forum 25(3):567–576
Han Q, Han L, Wang E, Yang J (2013) Dual watermarking for image tamper detection and self-recovery. In: Proc. of the 9th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 33–36
Hu W-C, Chen W-H (2013) Effective forgery detection using DCT + SVD-based watermarking for region of interest in key frames of vision-based surveillance. Int J Comput Sci Eng 8(4):297–305
Hu W-C, Chen W-H, Huang D-Y, Yang C-Y (2012) Novel detection of image forgery for exchanged foreground and background using image watermarking based on alpha matte. In: Proc. of the 6th International Conference on Genetic and Evolutionary Computing, pp. 245–248
Hu W-C, Chen W-H, Yang C-Y (2012) Robust image watermarking based on discrete wavelet transform-discrete cosine transform-singular value decomposition. J Electron Imaging 21(3):033005(1)–033005(7)
Hu W-C, Hsu J-F (2013) Automatic spectral video matting. Pattern Recogn 46(4):1183–1194
Hu W-C, Jhu J-J, Lin C-P (2012) Unsupervised and reliable image matting based on modified spectral matting. J Vis Commun Image Represent 23(4):665–676
Huang D-Y, Lin T-W, Hu W-C, Chou C-H (2013) Boosting scheme for detecting region duplication forgery in digital images. In: Proc. of the 7th International Conference on Genetic and Evolutionary Computing, pp. 125–133
Huang Y, Lu W, Sun W, Long D (2011) Improved DCT based detection of copy-move forgery in images. Forensic Sci Int 206(1–3):178–184
Lai C-C (2011) A digital watermarking scheme based on singular value decomposition and tiny genetic algorithm. Digit Signal Process 21:522–527
Lai C-C, Tsai C-C (2010) Digital image watermarking using discrete wavelet transform and singular value decomposition. IEEE Trans Instrum Meas 59:3060–3063
Levin A, Lischinski D, Weiss Y (2008) A closed-form solution to natural image matting. IEEE Trans Pattern Anal Mach Intell 30(2):228–242
Levin A, Rav-Acha A, Lischinski D (2008) Spectral matting. IEEE Trans Pattern Anal Mach Intell 30(10):1699–1712
Li L, Li S, Zhu H, Chu S-C, Roddick JF, Pan J-S (2013) An efficient scheme for detecting copy-move forged images by local binary patterns. J Inf Hiding Multimedia Signal Process 4(1):46–56
Lin G-S, Chang M-K, Chen Y-L (2011) A passive-blind forgery detection scheme based on content-adaptive quantization table estimation. IEEE Trans Circ Syst Video Technol 21(4):421–434
Lin Z, He J, Tang X, Tang CK (2009) Fast, automatic and fine-grained tampered JPEG image detection via DCT coefficient analysis. Pattern Recogn 42(11):2492–2501
Liu K-C (2012) Colour image watermarking for tamper proofing and pattern-based recovery. IET Image Process 6(5):445–454
Loukhaoukha K, Chouinard JY (2010) On the security of ownership watermarking of digital images based on SVD decomposition. J Electron Imaging 19(1):013007(1)–013007(9)
Mahdian B, Saic S (2009) Using noise inconsistencies for blind image forensics. Image Vis Comput 27(10):1497–1503
Ng A, Jordan M, Weiss Y (2001) On spectral clustering: analysis and an algorithm. Adv Neural Inf Process Syst 14:849–856
Rykaczewski R (2007) Comments on An SVD-based watermarking scheme for protecting rightful ownership. IEEE Trans Multimedia 9(2):421–423
Wang J, Cohen MF (2007) Image and video matting: a survey. Found Trends Comput Graph Vis 3(2):1–78
Zhang X-P, Li K (2005) Comments on an SVD-based watermarking scheme for protecting rightful ownership. IEEE Trans Multimedia 7(2):593–594
Acknowledgment
This paper has been supported by the National Science Council, Taiwan, under grant no. NSC102-2221-E-346-007. The authors wish to express the appreciation to Prof. Chih-Chin Lai and Prof. Zhouchen Lin for their help with the experiments. The authors also gratefully acknowledge the helpful comments and suggestions of reviewers, which have improved the quality and presentation.
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Hu, WC., Chen, WH., Huang, DY. et al. Effective image forgery detection of tampered foreground or background image based on image watermarking and alpha mattes. Multimed Tools Appl 75, 3495–3516 (2016). https://doi.org/10.1007/s11042-015-2449-0
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DOI: https://doi.org/10.1007/s11042-015-2449-0