数字图像取证技术的设计与实现
发布时间：2019-01-11 11:35
【摘要】：随着图像处理技术的迅速发展,对数字图像(自然图像)内容的篡改变得越来越容易,各类虚假图像频繁出现,使得数字图像可靠性,稳健性遭到严重损害。因为很多数字图像摄取设备并不具备嵌入数字水印功能,所以基于数字水印的主动取证技术受到很大限制,数字图像盲取证技术因此应运而生。数字图像篡改盲取证是在对原始图像没有任何先验知识,不对原始图像进行任何事先处理的情况下,对数字图像从被数字相机拍摄以后没有经过篡改的取证。数字图像盲取证技术主要应用于检测法庭上作证的照片、媒体上出现的照片是否真实可靠,还原出模糊退化图像的内容作为法庭证据等。这是一门刚刚兴起的技术,随着数字图像越来越广泛的应用,数字图像盲取证技术也会有越来越广阔的应用前景。本文主要通过对图像篡改过程中拼接痕迹的检测技术,实现了两种检测图像是否被篡改的方法。第一种方法利用图像块之间的特征值来进行相互比较,并判别出同幅图像中相似的图块,此部分即可判断为经过复制粘贴篡改的部分。第二种检测方法是基于图像边缘模糊篡改检测,利用一个滤波器实现对图像的边缘模糊的检测。经过实验证明,以上两种方法均能成功检测出同一幅图像中的复制粘贴篡改部分。
[Abstract]:With the rapid development of image processing technology, the tampering of digital image (natural image) has become more and more easy, and various kinds of false images appear frequently, which seriously damages the reliability and robustness of digital image. Because many digital image acquisition devices do not have the function of embedding digital watermarking, the active forensics technology based on digital watermarking is greatly restricted, so digital image blind forensics technology emerges as the times require. Blind forensics of digital image tampering is to obtain evidence without any prior knowledge of the original image and any prior processing of the original image, and the digital image has not been tampered with since it was taken by the digital camera. Blind digital image forensics technology is mainly used to detect the evidence in court, whether the photos appear in the media are true and reliable, and to restore the content of the blurred degraded image as court evidence. This is a newly emerging technology. With the more and more extensive application of digital image, blind forensics of digital image will have more and more broad application prospects. In this paper, two methods of detecting whether the image is tampered with or not are realized by detecting the stitching marks in the process of image tampering. The first method makes use of the eigenvalues of the image blocks to compare with each other and to distinguish the similar blocks in the same image. This part can be judged as the part that has been tampered with by copy and paste. The second method is based on image edge fuzzy tamper detection, using a filter to detect image edge blur. The experiments show that the two methods can detect the copy and paste tampering part of the same image successfully.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP391.41
[Abstract]:With the rapid development of image processing technology, the tampering of digital image (natural image) has become more and more easy, and various kinds of false images appear frequently, which seriously damages the reliability and robustness of digital image. Because many digital image acquisition devices do not have the function of embedding digital watermarking, the active forensics technology based on digital watermarking is greatly restricted, so digital image blind forensics technology emerges as the times require. Blind forensics of digital image tampering is to obtain evidence without any prior knowledge of the original image and any prior processing of the original image, and the digital image has not been tampered with since it was taken by the digital camera. Blind digital image forensics technology is mainly used to detect the evidence in court, whether the photos appear in the media are true and reliable, and to restore the content of the blurred degraded image as court evidence. This is a newly emerging technology. With the more and more extensive application of digital image, blind forensics of digital image will have more and more broad application prospects. In this paper, two methods of detecting whether the image is tampered with or not are realized by detecting the stitching marks in the process of image tampering. The first method makes use of the eigenvalues of the image blocks to compare with each other and to distinguish the similar blocks in the same image. This part can be judged as the part that has been tampered with by copy and paste. The second method is based on image edge fuzzy tamper detection, using a filter to detect image edge blur. The experiments show that the two methods can detect the copy and paste tampering part of the same image successfully.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP391.41
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