Unified Performance Evaluation Method for Perceptual Image Hashing

被引:20
|
作者
Li, Xinran [1 ]
Qin, Chuan [1 ]
Wang, Zichi [2 ]
Qian, Zhenxing [3 ]
Zhang, Xinpeng [3 ]
机构
[1] Univ Shanghai Sci & Technol, Sch Opt Elect & Comp Engn, Shanghai 200093, Peoples R China
[2] Shanghai Univ, Sch Commun & Informat Engn, Shanghai 200444, Peoples R China
[3] Fudan Univ, Sch Comp Sci, Shanghai 200433, Peoples R China
基金
中国国家自然科学基金; 上海市自然科学基金;
关键词
Feature extraction; Robustness; Transforms; Security; Dimensionality reduction; Principal component analysis; Image coding; Image hashing; evaluation; universality; order relationship analysis; RING PARTITION; ROBUST;
D O I
10.1109/TIFS.2022.3161149
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In recent decades, a large number of perceptual image hashing schemes have been designed to secure the authenticity and integrity of digital images. However, the feasible criterion to evaluate the performances of hashing schemes has not been developed yet. To this end, a unified performance evaluation method for perceptual image hashing schemes is proposed in this paper. The proposed evaluation method contains six modules: robustness, discrimination, tampering detection, security, computational efficiency and hash length. The order relationship analysis (ORA) is employed to assign the score proportion of each module in accordance with the relative importance of performance, which allows the customizability of user. The real scores of modules and the outputted final score can reflect the performances of perceptual image hashing schemes intuitively and convincingly. Experimental results demonstrate that the proposed evaluation method is practical and effective for the complete and comprehensive evaluation of perceptual image hashing schemes.
引用
收藏
页码:1404 / 1419
页数:16
相关论文
共 50 条
  • [1] Perceptual image hashing via feature points: Performance evaluation and tradeoffs
    Monga, Vishal
    Evans, Brian L.
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2006, 15 (11) : 3452 - 3465
  • [2] PERCEPTUAL SPEECH HASHING AND PERFORMANCE EVALUATION
    Jiao, Yuhua
    Ji, Liping
    Niu, Xiamu
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2010, 6 (3B): : 1447 - 1458
  • [3] Performance analysis of image content identification on perceptual hashing
    Pan, Hui
    Zheng, Gang
    Hu, Xiaohui
    Ma, Hengtai
    Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics, 2012, 24 (07): : 925 - 931
  • [4] A New Distance Measurement Method for Perceptual Image Hashing
    Li, Xinran
    Qin, Chuan
    Wang, Zichi
    Zhang, Xinpeng
    Tang, Zhenjun
    IETE TECHNICAL REVIEW, 2024, 41 (06) : 650 - 658
  • [5] A Multi-channel Combination Method of Image Perceptual Hashing
    Zhang, Hui
    Zhang, Haibin
    Li, Qiong
    Niu, Xiamu
    NCM 2008: 4TH INTERNATIONAL CONFERENCE ON NETWORKED COMPUTING AND ADVANCED INFORMATION MANAGEMENT, VOL 2, PROCEEDINGS, 2008, : 87 - 90
  • [6] Perceptual hashing for image authentication: A survey
    Du, Ling
    Ho, Anthony T. S.
    Cong, Runmin
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 2020, 81
  • [7] Secure and robust image perceptual hashing
    Information Security Research Center, Dalian University of Technology, Dalian 116024, China
    不详
    Dongnan Daxue Xuebao, 2007, SUPPL. (188-192):
  • [8] Perceptual hashing for SAR image segmentation
    Ji, Jian
    Yao, Yafeng
    Wei, Jiajie
    Quan, Yining
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2019, 40 (10) : 3672 - 3688
  • [9] Digital Image Copyright Protection Method Based on Blockchain and Perceptual Hashing
    Zhang, Qiu-Yu
    Wu, Guo-Rui
    International Journal of Network Security, 2023, 25 (01) : 10 - 24
  • [10] Clustering algorithms for perceptual image hashing
    Monga, V
    Banerjee, A
    Evans, BL
    IEEE 11TH DIGITAL SIGNAL PROCESSING WORKSHOP & 2ND IEEE SIGNAL PROCESSING EDUCATION WORKSHOP, 2004, : 283 - 287