Abstract
In this paper, an adaptive method for copy-move forgery detection and localization in digital images is proposed. The method employs wavelet transform with non constant Q factor and characterizes image pixels through the multiscale behavior of corresponding wavelet coefficients. The detection of forged regions is then performed by considering similar those pixels having the same multiscale behavior. The method is pointwise and the length of pixel features vector is image dependent, allowing for a more precise and fast detection of forged regions. The qualitative and quantitative evaluation of the experimental results reveals that the proposed method outperforms some existing transform-based methods in terms of performance and execution time.
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Acknowledgments
This research has been supported by the GNCS (Gruppo Nazionale di CalcoloScientifico) of the INdAM (IstitutoNazionale di Alta Matematica) and partially funded by Regione Lazio, POR FESR Aerospace and Security Programme, Project COURIER - COUntering RadIcalism InvEstigation platform - CUP F83G17000860007.
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Bruni, V., Ramella, G., Vitulano, D. (2019). An Adaptive Copy-Move Forgery Detection Using Wavelet Coefficients Multiscale Decay. In: Vento, M., Percannella, G. (eds) Computer Analysis of Images and Patterns. CAIP 2019. Lecture Notes in Computer Science(), vol 11678. Springer, Cham. https://doi.org/10.1007/978-3-030-29888-3_38
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