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PERFORMANCE ANALYSIS OF FORGERY DETECTION OF JPEG IMAGE COMPRESSION

机译:JPEG图像压缩伪造检测性能分析

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The proposed forensic algorithm to discriminate between original and forged regions in JPEG images, under the hypothesis that the tampered image presents a double JPEG compression, either aligned (A-DJPG) or nonaligned (NA-DJPG). Unlike previous approaches, the proposed algorithm does not need to manually select a suspect region in order to test the presence or the absence of double compression artifacts. Based on an improved and unified statistical model characterizing the artifacts that appear in the presence of both A-DJPG or NA-DJPG, the proposed algorithm automatically computes a likelihood map indicating the probability for each 8 × 8 discrete cosine transform block of being doubly compressed. The validity of the proposed approach has been assessed by evaluating the performance of a detector based on thresholding the likelihood map, considering different forensic scenarios. The effectiveness of the proposed method is also confirmed by tests carried on realistic tampered images. An interesting property of the proposed Bayesian approach is that it can be easily extended to work with traces left by other kinds of processing.
机译:所提出的法医算法为了区分JPEG图像中的原始和伪造区域,在篡改图像呈现双JPEG压缩的假设下,对齐(A-DJPG)或非基准(NA-DJPG)。与先前的方法不同,该算法不需要手动选择可疑区域以测试双压缩伪像的存在或不存在。基于特征和统一的统计模型,其特征在于在A-DJPG或NA-DJPG的存在中出现的伪影,所提出的算法自动计算指示每8×8离散余弦变换块的概率映射的似然映射是双压缩的。考虑到不同的法医场景,通过评估了探测器的性能来评估所提出的方法的有效性。所提出的方法的有效性也通过在现实篡改图像上进行的测试确认。拟议的贝叶斯方法的一个有趣的财产是,它可以很容易地扩展到与其他类型的处理留下的痕迹一起使用。

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