Abstract
Image forgery detection is currently one of the interested research fields of image processing. Copy-Move (CM) forgery is one of the most commonly techniques. In this paper, we propose an efficient methodology for fast CM forgery detection. The proposed method accelerates blocking matching strategy. Firstly, the image is divided into fixed-size overlapping blocks then Discrete Cosine Transform (DCT) is applied to each block to represent its features, which are used to indirectly compare the blocks. After sorting the blocks based on DCT coefficients, a distance is measured between nearby blocks to denote their similarity. The proposed Fan Search (FS) algorithm starts once a duplicated block is detected. Instead of exhaustive search for all blocks, the nearby blocks of the detected block are examined first in a spiral order. The experimental results demonstrate that the proposed method can detect the duplicated regions efficiently, and reduce processing time up to 75% less than other previous works.
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Fadl, S.M., Semary, N.A., Hadhoud, M.M. (2014). Fan Search for Image Copy-Move Forgery Detection. In: Hassanien, A.E., Tolba, M.F., Taher Azar, A. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2014. Communications in Computer and Information Science, vol 488. Springer, Cham. https://doi.org/10.1007/978-3-319-13461-1_18
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DOI: https://doi.org/10.1007/978-3-319-13461-1_18
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13460-4
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