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A Novel Method for Block Size Forensics Basde on Morphological Operations

机译:基于形态学运算的区块大小取证的新方法

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Passive forensics analysis aims to find out how multimedia data is acquired and processed without relying on pre-embedded or pre-registered information. Since most existing compression schemes for digital images are based on block processing, one of the fundamental steps for subsequent forensics analysis is to detect the presence of block artifacts and estimate the block size for a given image. In this paper, we propose a novel method for blind block size estimation. A 2 x 2 cross-differential filter is first applied to detect all possible block artifact boundaries, morphological operations are then used to remove the boundary effects caused by the edges of the actual image contents, and finally maximum-likelihood estimation (MLE) is employed to estimate the block size. The experimental results evaluated on over 1300 nature images show the effectiveness of our proposed method. Compared with existing gradient-based detection method, our method achieves over 39% accuracy improvement on average.
机译:被动取证分析旨在找出如何在不依赖预先嵌入或预先注册的信息的情况下获取和处理多媒体数据。由于大多数现有的数字图像压缩方案都基于块处理,因此后续取证分析的基本步骤之一是检测块伪像的存在并估计给定图像的块大小。在本文中,我们提出了一种新的盲块大小估计方法。首先应用2 x 2交叉微分滤波器来检测所有可能的块伪像边界,然后使用形态学运算来消除由实际图像内容的边缘引起的边界效应,最后采用最大似然估计(MLE)估计块大小。在1300多个自然图像上评估的实验结果表明了该方法的有效性。与现有的基于梯度的检测方法相比,我们的方法平均可将准确性提高39%以上。

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