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A METHOD AND APPARATUS FOR A NATURAL IMAGE MODEL BASED APPROACH TO IMAGE SPLICING/TAMPERING DETECTION

机译:基于自然图像模型的图像拼接/篡改检测方法和装置

摘要

Embodiments of the invention are directed toward methods for an effective blind, passive, splicing/tampering detection. The methods of the various embodiments of the invention use a natural image model to detect image splicing/tampering with a model that is based on statistical features extracted from a given test image and multiple 2-D arrays generated by applying the block discrete cosine transform (BDCT) with several different block-sizes to the test images. Experimental results have demonstrated that the new splicing detection scheme outperforms state-of-the-art methods by a significant margin when applied to the Columbia Image Splicing Detection Evaluation Dataset.
机译:本发明的实施例针对用于有效盲,被动,拼接/篡改检测的方法。本发明各个实施例的方法使用自然图像模型来检测图像的拼接/篡改,该模型基于从给定测试图像中提取的统计特征以及通过应用块离散余弦变换而生成的多个二维数组( BDCT)和测试图像具有几种不同的块大小。实验结果表明,当将新的拼接检测方案应用于Columbia图像拼接检测评估数据集时,其性能远远优于最新技术。

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