基于直方图特征的盲中值滤波检测

Xinlu Gui, Xiaolong Li, Wenfa Qi, Bin Yang
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引用次数: 6

摘要

近年来,中值滤波(MF)检测器作为一种识别图像编辑过程的法医工具引起了人们的广泛关注。本文提出了一种基于直方图特征的数字图像MF盲检测方法。直方图是最基础的资源,可以呈现大部分的图像信息,我们建议直接利用直方图,取残差图像中直方图最高的几个箱子作为特征进行分类。为此,引入多尺度旋转和对称不变模式作为卷积核,用于各种残差图像的计算和直方图的生成。在大型图像数据库上进行了大量的实验,验证了所提方法的有效性,实验结果表明,仅用21个特征,所提方法就优于目前一些最先进的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blind median filtering detection based on histogram features
Recently, the median filtering (MF) detector has attracted much interest as a forensic tool to identify image editing process. In this paper, we propose a novel method for the blind detection of MF in digital images based on the histogram features. As histograms are fundamental resources and can present most image information, we propose to directly utilize them by taking several highest histogram bins of the residual images as features to carry out classification. To this end, multi-scaled rotation and symmetry invariant patterns are introduced as convolution kernels for various residual images calculation and histograms generation. The effectiveness of the proposed method is verified by extensive experiments on a large image database, and the experimental results demonstrate that, with only 21 features, the proposed method outperforms some state-of-the-art works.
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