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Identifying Forged Images Using Image Metadata

机译:使用图像元数据识别伪造的图像

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摘要

Nowadays, we receive, send and click a number of images frequently. Multimedia messages especially images can be easily transferred to anyone in no time and no cost just like text messages. There are many software easily available that can modify an image. With such a wide usage of images in communication networks it becomes difficult to conclude if an image is an original one or a forged one. This paper proposes the usage of image metadata, which is much smaller in size as compared to contents of an image, to authenticate an image. Further, the architecture of a system using a neural network is proposed which extracts attributes from the metadata of an image to predict if an image is an original one or a forged one. The system is also capable of predicting the operation applied and the software/tool used to modify the original image in case of a forged image. Experiments have been conducted on JPEG images which are modified with operations like Crop, Rotate, Resize, Compress, Compress_Rotate and Crop_Rotate to validate our system.
机译:如今,我们经常收到,发送和点击许多图像。多媒体消息尤其可以轻松地将任何人转移到任何时间,也可以像短信一样。有许多软件可轻松可用,可以修改图像。利用这种通信网络中的图像的广泛使用,如果图像是原始的一个或伪造的图像,则难以结束。本文提出了与图像内容相比的图像元数据的使用,该图像元数​​据尺寸小得多,以验证图像。此外,提出了使用神经网络的系统的体系结构,其从图像的元数据中提取属性以预测图像是原始的一个或伪造的。该系统还能够预测应用的操作和用于在伪造图像的情况下修改原始图像的软件/工具。在JPEG图像上进行了实验,该图像用裁剪,旋转,调整大小,压缩,compress_rootate和crop_rotate等操作来修改,以验证我们的系统。

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