[1]文振焜,陈斌,吴惠思.基于自适应哈希算法的直播视频篡改检测[J].深圳大学学报理工版,2017,34(2):165-172.
 Wen Zhenkun,Chen Bin,and Wu Husi. Tamper detection based on adaptive hashing algorithm for live video streaming[J].Journal of Shenzhen University Science and Engineering,2017,34(2):165-172.
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基于自适应哈希算法的直播视频篡改检测()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第34卷
期数:
2017年第2期
页码:
165-172
栏目:
电子与信息科学
出版日期:
2017-03-20

文章信息/Info

Title:
 Tamper detection based on adaptive hashing algorithm for live video streaming
作者:
 文振焜陈斌吴惠思
 深圳大学计算机与软件学院,广东深圳 518060
Author(s):
Wen Zhenkun Chen Bin and Wu Husi
 College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060,Guangdong Province, P.R.China
关键词:
 计算机感知自适应哈希算法视频篡改视频内容保护实时视频
Keywords:
 computer perception adaptive hashing algorithm video forgery video content protection real-time video
分类号:
TP 37
文献标志码:
A
摘要:
 提出基于视频压缩帧的自适应哈希算法,并将该算法用于实时视频篡改检测.根据帧内数据长度划分非固定步长区间,提取帧的空间结构特征,使用哈希量化形成固定长度的密钥.实验结果表明,该算法达到实时性要求,表现出较好的鲁棒性和区分性,通过统计视频画面组的密钥相似度,能有效检测视频篡改.
Abstract:
 A new adaptive hashing algorithm based on video compression frames for real-time detection of the tampered video streaming is proposed. According to data length of a frame, the algorithm divides the frame into a number of intervals with different step-size and extracts theframe feature in spatial structure. The feature is quantized to generate the secret key. The experimental results show that the algorithm can meet real-time requirement and is robust and discriminative. It can detect accurately a video tampered through counting the similarity of keys in each group of pictures in the video.

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更新日期/Last Update: 2017-03-03