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投稿时间：2020-03-18
投稿时间：2020-03-18
中文摘要: 现有数字图像篡改被动检测技术相关综述对传统检测手段的描述详实细致,但缺乏对以深度学习为导向的利用卷积神经网络检测技术的系统介绍。针对数字图像篡改被动检测问题,就基于特征提取的传统篡改检测和基于卷积神经网络的篡改检测两个主要研究方向进行了阐述,分析和总结了其主要研究工作和相关算法,并在此基础上指出了数字图像篡改被动检测未来可能的发展趋势。
Abstract:The existing passive detection technology of digital image tampering mainly focuses on the traditional detection methods,and lacks the systematic introduction of the detection technology based on the deep learning using convolutional neural network.Aiming at the problem of passive detection of digital image tampering,this paper expounds two main research directions:traditional tamper detection based on feature extraction and tamper detection based on convolutional neural network,analyzes and summarizes the main research work and related algorithms.On this basis,it points out the possible development trend of passive detection of digital image tampering in the future.
文章编号：202202014 中图分类号：TP391 文献标志码：
基金项目:国家自然科学基金面上项目(61772327);国家自然科学基金重点项目(61532021)。
引用文本：
刘正,田秀霞.数字图像篡改被动检测技术综述[J].上海电力大学学报,2022,38(2):189-198.
LIU Zheng,TIAN Xiuxia.An Overview of Passive Detection Technology for Digital Image Tampering[J].Journal of Shanghai University of Electric Power,2022,38(2):189-198.
刘正,田秀霞.数字图像篡改被动检测技术综述[J].上海电力大学学报,2022,38(2):189-198.
LIU Zheng,TIAN Xiuxia.An Overview of Passive Detection Technology for Digital Image Tampering[J].Journal of Shanghai University of Electric Power,2022,38(2):189-198.