Video Hashing with DCT and NMF. (20th August 2019)

• Record Type: Journal Article
• Authors: Tang, Zhenjun; Chen, Lv; Yao, Heng; Zhang, Xianquan; Yu, Chunqiang
• Editors: Murtagh, Fionn
• Is Part Of: Computer journal. Volume 63:Number 7(2020)
• Page Start: 1017
• Page End: 1030
• Publication Date: 2019-08-20
• Subjects: video hashing -- random partition -- discrete cosine transform -- dominant DCT coefficients -- non-negative matrix factorization -- video copy detection; Computers -- Periodicals; 005.1
• DOI: 10.1093/comjnl/bxz060
• Languages: English
• ISSNs: 0010-4620

Abstract

Abstract: 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.