Texture and steerability based image authentication

S. Babu, C. Rao
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引用次数: 18

Abstract

Copy-Move Forgery Detection (CMFD) method is useful for identifying copy and pasted portions in an image. CMFD has demand in forensic investigation, legal evidence and in many other fields. In this paper, the gists of different newly arrived methodologies in current literature are discussed. Some existing methodologies can be able to localize the forged region and some are not. An efficient method for localization of copy move forgery is proposed in this work for identifying forgery. In the proposed methodology, CMFD is achieved by giving suspected image to Steerable Pyramid Transform (SPT), Local Binary Pattern (LBP) is applied on each oriented subband obtained from SPT to extract feature set, then it is used to trained Support Vector Machine (SVM) to classify images into forged or not. Then localization process is carried out on forged images. Results of proposed methodology are showing robustness even though the forged image has undergone some post processing attacks viz., rotation, flip, JPEG compression.
基于纹理和可操纵性的图像认证
复制-移动伪造检测(CMFD)方法用于识别图像中的复制和粘贴部分。CMFD在法医调查、法律证据和其他许多领域都有需求。本文对当前文献中出现的各种新方法的要点进行了讨论。现有的方法中,有的能够对伪造区域进行定位,有的则不能。本文提出了一种有效的复制移动伪造定位方法,用于识别伪造。在该方法中,将可疑图像进行可操纵金字塔变换(SPT)来实现CMFD,在SPT得到的每个方向子带上应用局部二值模式(LBP)来提取特征集,然后将其用于训练的支持向量机(SVM)来对图像进行伪造和非伪造分类。然后对伪造图像进行定位处理。结果表明,即使伪造图像经历了一些后处理攻击,即旋转、翻转、JPEG压缩,所提出的方法仍显示出鲁棒性。
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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