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Passive image tamper detection based on Fast Retina Key Point Descriptor

机译:基于快速视网膜关键点描述符的被动图像篡改检测

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摘要

Images are major resource for information owing to their wide use and availability in the internet. Ensuring trustworthiness for image content is a primary objective of image forensic discovery. Copy-move is one of the main and frequently used tampering practices for reproducing or concealing precise area of an image. Most of existing methods deploy block matching technique to match and locate the tampered region which leads high computational complexity. This article introduces a robust technique to discover copy-move tampering with Fast Retina Key Point Descriptor (FREAK). Suspected image is preprocessed and FREAK feature descriptors around each Harris corner points were discovered. Detected FREAK features are mapped by means of KD-Tree algorithm. Experimental outcomes reveals that proposed technique efficiently detects copy-move tampered region even it is rotated, multi-pasted, blurred or brightness adjusted.
机译:由于图像在互联网上的广泛使用和可用性,图像是信息的主要资源。确保图像内容的可信度是图像取证发现的主要目的。复制移动是用于复制或隐藏图像精确区域的主要且经常使用的篡改方法之一。现有的大多数方法都采用块匹配技术来匹配和定位被篡改的区域,这导致了很高的计算复杂度。本文介绍了一种强大的技术,可以发现使用快速视网膜关键点描述符(FREAK)进行的复制移动篡改。对可疑图像进行预处理,并在每个哈里斯角点附近找到FREAK特征描述符。通过KD-Tree算法映射检测到的FREAK特征。实验结果表明,所提出的技术即使旋转,多粘贴,模糊或调节亮度也能有效检测出复制移动的篡改区域。

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