Image Forgery detection on cloud

A. James, E. Bijolin Edwin, Anjana M C, Angel Mary Abraham, Harsha Johnson
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引用次数: 3

Abstract

Every day many digital documents are produced and distributed by televisions, newspapers, magazines, and websites. In all these communication channels images play an important role in communicating the information. Today, it is very easy to manipulate digital images with the help of advanced computer, photo editing software, image processing techniques etc. So, verification of the authenticity of digital images has become a challenging problem. This paper is based on image forgery detection on cloud. Image forger detection is classified into two: passive and active. Active approach includes digital signature and watermarking whereas the Passive approach includes detection of the tampered area using copy move and splicing techniques. Here we are using Canny Edge Detection Algorithm which mainly uses splicing. In this paper, we are also comparing canny edge detection and SSIM. SSIM is more efficient compared to canny edge detector and it gives above 90 % accuracy.
云图像伪造检测
每天,电视、报纸、杂志和网站都会产生和传播许多数字文档。在所有这些通信渠道中,图像在信息传递中起着重要的作用。今天,在先进的计算机、照片编辑软件、图像处理技术等的帮助下,操纵数字图像非常容易。因此,数字图像的真实性验证成为一个具有挑战性的问题。本文是基于云的图像伪造检测。图像伪造检测分为被动检测和主动检测两种。主动方法包括数字签名和水印,而被动方法包括使用复制移动和拼接技术检测篡改区域。这里我们使用Canny边缘检测算法,主要使用拼接。本文还对canny边缘检测和SSIM进行了比较。与canny边缘检测器相比,SSIM的效率更高,准确率在90%以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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