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Subject: Computer Science
Title:
perceptual video hashing robust against geometric distortions
Author: Xiang ShiJun ; Yang JianQuan ; Huang JiWu
Keyword: video hashing ; geometric distortion ; histogram ; Gaussian filtering
Source: SCIENCE CHINA-INFORMATION SCIENCES
Issued Date: 2012
Volume: 55, Issue:7, Pages:1520-1527
Indexed Type: SCI
Department: Huang JiWu Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510275 Guangdong Peoples R China. Xiang ShiJun Jinan Univ Sch Informat Sci & Technol Guangzhou 510632 Guangdong Peoples R China. Yang JianQuan Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen 518055 Peoples R China. Xiang ShiJun Chinese Acad Sci State Key Lab Informat Secur Inst Software Beijing 100049 Peoples R China.
Sponsorship: National Natural Science Foundation of China 60903177, 61003297; National Basic Research Program of China 2011CB302204; Fundamental Research Funds for the Central Universities 21611408
Abstract: In this paper, we propose a robust perceptual hashing algorithm by using video luminance histogram in shape. The underlying robustness principles are based on three main aspects: 1) Since the histogram is independent of position of a pixel, the algorithm is resistant to geometric deformations; 2) the hash is extracted from the spatial Gaussian-filtering low-frequency component for those common video processing operations such as noise corruption, low-pass filtering, lossy compression, etc.; 3) a temporal Gaussian-filtering operation is designed so that the hash is resistant to temporal desynchronization operations, such as frame rate change and dropping. As a result, the hash function is robust to common geometric distortions and video processing operations. Experimental results show that the proposed hashing strategy can provide satisfactory robustness and uniqueness.
English Abstract: In this paper, we propose a robust perceptual hashing algorithm by using video luminance histogram in shape. The underlying robustness principles are based on three main aspects: 1) Since the histogram is independent of position of a pixel, the algorithm is resistant to geometric deformations; 2) the hash is extracted from the spatial Gaussian-filtering low-frequency component for those common video processing operations such as noise corruption, low-pass filtering, lossy compression, etc.; 3) a temporal Gaussian-filtering operation is designed so that the hash is resistant to temporal desynchronization operations, such as frame rate change and dropping. As a result, the hash function is robust to common geometric distortions and video processing operations. Experimental results show that the proposed hashing strategy can provide satisfactory robustness and uniqueness.
Language: 英语
WOS ID: WOS:000305330600004
Citation statistics:
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/15075
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Xiang ShiJun,Yang JianQuan,Huang JiWu. perceptual video hashing robust against geometric distortions[J]. SCIENCE CHINA-INFORMATION SCIENCES,2012-01-01,55(7):1520-1527.
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