摘要
为了克服现有数字视频取证算法识别准确率低、定位能力差等缺点,提出一种具有高识别率且定位准确的基于Inception-V3网络的二级分类取证算法.在第一级分类器中提出简单的阈值判断方法来区分原始和篡改视频,第二级分类器将采用Inception-V3网络的稠密卷积核结构来自动提取篡改视频帧的高维多尺度特征.高维多尺度特征有助于提升篡改视频帧的识别率.实验结果表明,本文提出的算法不仅能准确地检测出篡改视频,还能从篡改视频中精确定位出篡改帧.
In order to overcome the shortcomings(e.g. low recognition accuracy and poor localization ability) of existing video forensics techniques, a two-stage algorithm is proposed based on Inception-V3 network, whose advantage lies in the fact that it can accurately identify a forged video and locate its forged frames. After an extensive research, it is found that the average value of all the pixels in a pristine video sequence is always larger than its forged one after the video sequence is processed via several operations such as high-pass filtering and convolution. To this end, in the first stage, a simple algorithm is proposed in which a predefined threshold is employed to distinguish a forged video and a pristine video. Considering the fact that features of each frame need to be extracted manually in existing algorithms, the dense convolution kernel structure of Inception-V3 network is adopted in the second stage to automatically extract high dimensional and multi-scale features of each forged frame.Inception-V3 network can accurately locate forged frames in a forged video since dimensional and multi-scale features can more adequately express the input information. The experiments show that the proposed method performs very well both in forged video identification and forged frame localization.
作者
翁韶伟
彭一航
危博
易林
叶武剑
Weng Shao-wei;Peng Yi-hang;Wei Bo;Yi Lin;Ye Wu-jian(School of Information Engineering,Guangdong University of Technology,Guangzhou 510006,China;Guangdong Key Laboratory of Intelligent Information Processing,Shenzhen 518060,China)
出处
《广东工业大学学报》
CAS
2019年第6期16-23,共8页
Journal of Guangdong University of Technology
基金
国家自然科学基金资助项目(61872095,61872128,61571139,61201393)
广东省智能信息处理重点实验室、深圳市媒体信息内容安全重点实验室2018年开放基金课题(ML-2018-03)
广东省信息安全技术重点实验室开放课题基金资助(2017B030314131)
广州市珠江科技新星专题(2014J2200085)
