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首页> 外文期刊>The Open Artificial Intelligence Journal >A Comparison Study on Copy-Cover Image Forgery Detection
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A Comparison Study on Copy-Cover Image Forgery Detection

机译:复制封面图像伪造检测的比较研究

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Due to rapid advances and availabilities of powerful image processing software, digital images are easy to manipulate and modify for ordinary people. This makes it more and more difficult for a viewer to check the authenticity of a given digital image. For digital photographs to be used as evidence in law issues or to be circulated in mass media, it is inevitably needed to identify whether an image is authentic or not. In this paper, we discuss the techniques of copy-cover image forgery and compare four detection methods for copy-cover forgery detection, which are based on PCA, DCT, spatial domain, and statistical domain. We investigate their effectiveness and sensitivity under the influences of Gaussian blurring and lossy JPEG compressions. It is concluded that the PCA method outperforms the others in terms of time complexity and accuracy. In JPEG compression simulation, its true positive rate is above 90% and false positive rate is above 99%. In Gaussian blurring simulation, its true positive rate is above 77% and false positive rate is above 99%.
机译:由于功能强大的图像处理软件的迅速发展和可用性,数字图像对于普通人来说很容易操作和修改。这使得观看者越来越难检查给定数字图像的真实性。对于要在法律问题上用作证据或在大众媒体中传播的数码照片,不可避免地需要识别图像是否真实。在本文中,我们讨论了复制封面图像伪造技术,并比较了四种基于PCA,DCT,空间域和统计域的复制封面伪造检测方法。我们研究了它们在高斯模糊和有损JPEG压缩的影响下的有效性和敏感性。结论是,在时间复杂度和准确性方面,PCA方法优于其他方法。在JPEG压缩模拟中,其正确率大于90%,错误率大于99%。在高斯模糊模拟中,其真实阳性率高于77%,而错误阳性率高于99%。

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