Abstract
In the modern world, digital images are the sources of information. These sources can be manipulated by image processing and editing software. Image authenticity becomes a socially relevant issue in image forensics. Copy move is a main digital image forgery attack where the region of image is copied and pasted in the same image at different locations for hiding the information. This paper presents an analysis of accuracy in detecting copy move forgery based on different types of wavelet transform. For each wavelet transform, analysis is done at different levels of decomposition. The result indicates that both stationary wavelet transform (SWT) and lifting wavelet transform (LWT) work more effectively as compared to discrete wavelet transform (DWT).
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Melvi, C.V., Sathish Kumar, C., Saji, A.J., Varghese, J. (2018). Performance Analysis of Wavelet Transform Based Copy Move Forgery Detection. In: Zelinka, I., Senkerik, R., Panda, G., Lekshmi Kanthan, P. (eds) Soft Computing Systems. ICSCS 2018. Communications in Computer and Information Science, vol 837. Springer, Singapore. https://doi.org/10.1007/978-981-13-1936-5_15
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DOI: https://doi.org/10.1007/978-981-13-1936-5_15
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