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A Robust Forensic Hash Component for Image Alignment

机译:用于图像对齐的强大的法医哈希组件

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The distribution of digital images with the classic and newest technologies available on Internet (e.g., emails, social networks, digital repositories) has induced a growing interest on systems able to protect the visual content against malicious manipulations that could be performed during their transmission. One of the main problems addressed in this context is the authentication of the image received in a communication. This task is usually performed by localizing the regions of the image which have been tampered. To this aim the received image should be first registered with the one at the sender by exploiting the information provided by a specific component of the forensic hash associated with the image. In this paper we propose a robust alignment method which makes use of an image hash component based on the Bag of Visual Words paradigm. The proposed signature is attached to the image before transmission and then analyzed at destination to recover the geometric transformations which have been applied to the received image. The estimator is based on a voting procedure in the parameter space of the geometric model used to recover the transformation occurred to the received image. Experiments show that the proposed approach obtains good margin in terms of performances with respect to state-of-the art methods.
机译:具有Internet上可用的经典和最新技术的数字图像的分发(例如电子邮件,社交网络,数字存储库)已引起人们对能够保护视觉内容免受传输过程中可能进行的恶意操纵的系统的关注。在这种情况下解决的主要问题之一是对在通信中接收到的图像的认证。通常通过定位已被篡改的图像区域来执行此任务。为此,首先应通过利用与图像相关联的法医哈希的特定组件提供的信息,在发送者处将接收到的图像注册到该图像。在本文中,我们提出了一种鲁棒的对齐方法,该方法利用了基于视觉单词袋范例的图像哈希组件。建议的签名在传输之前会附加到图像上,然后在目标位置进行分析以恢复已应用于接收图像的几何变换。估计器基于几何模型的参数空间中的表决过程,该过程用于恢复发生在接收图像上的变换。实验表明,相对于最新方法,该方法在性能方面具有良好的优势。

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