Video Hashing with DCT and NMF

被引：12

作者：

Tang, Zhenjun ^{[1
]}

Chen, Lv ^{[1
,2
]}

Yao, Heng ^{[3
,4
]}

Zhang, Xianquan ^{[1
]}

Yu, Chunqiang ^{[1
]}

机构：

[1] Guangxi Normal Univ, Guangxi Key Lab Multisource Informat Min & Secur, Guilin 541004, Peoples R China

[2] Minist Educ, Key Lab Aerosp Informat Secur & Trusted Comp, Wuhan 430072, Peoples R China

[3] Univ Shanghai Sci & Technol, Shanghai Key Lab Modern Opt Syst, Shanghai 200093, Peoples R China

[4] Univ Shanghai Sci & Technol, Engn Res Ctr Opt Instrument & Syst, Minist Educ, Shanghai 200093, Peoples R China

来源：

COMPUTER JOURNAL | 2020年 / 63卷 / 07期

基金：

中国国家自然科学基金;

关键词：

video hashing; random partition; discrete cosine transform; dominant DCT coefficients; non-negative matrix factorization; video copy detection; NONNEGATIVE MATRIX FACTORIZATION; RING PARTITION; IMAGE; TRANSFORM; ALGORITHM;

D O I：

10.1093/comjnl/bxz060

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Video hashing is a novel technique of multimedia processing and finds applications in video retrieval, video copy detection, anti-piracy search and video authentication. In this paper, we propose a robust video hashing based on discrete cosine transform (DCT) and non-negative matrix decomposition (NMF). The proposed video hashing extracts secure features from a normalized video via random partition and dominant DCT coefficients, and exploits NMF to learn a compact representation from the secure features. Experiments with 2050 videos are carried out to validate efficiency of the proposed video hashing. The results show that the proposed video hashing is robust to many digital operations and reaches good discrimination. Receiver operating characteristic (ROC) curve comparisons illustrate that the proposed video hashing outperforms some state-of-the-art algorithms in classification between robustness and discrimination.

引用

页码：1017 / 1030

页数：14

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