{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T00:12:07Z","timestamp":1777421527105,"version":"3.51.4"},"reference-count":93,"publisher":"Association for Computing Machinery (ACM)","issue":"7","funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2023YFF0905000"],"award-info":[{"award-number":["2023YFF0905000"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2025,7,31]]},"abstract":"<jats:p>Perceptual hashing is a cutting-edge technique in the field of digital multimedia security, which maps the perceptual content of multimedia information to a fixed-length hash sequence to achieve content authentication. This survey provides a systematic overview of the definition, basic steps, main characters, and application scenarios of perceptual hashing. According to the different authentication objects, representative schemes of perceptual image hashing, perceptual video hashing, and perceptual hashing for neural network models are introduced, respectively. Both perceptual image hashing and perceptual video hashing can be divided into classical methods-based schemes and learning-based schemes, where learning-based schemes can be subdivided into supervised and unsupervised. Classical methods-based image hashing schemes can be divided into four categories: local feature-based, transformation-based, statistical feature-based, and dimensionality reduction-based. Classical methods-based video hashing schemes are mainly categorized into spatial feature-based schemes and spatial-temporal feature-based schemes. Additionally, we introduce the dataset composition and hash distance metric strategies for perceptual hashing and analyze the performance of some representative schemes. Finally, we summarize the existing schemes and offer prospects for future research directions and development trends.<\/jats:p>","DOI":"10.1145\/3727880","type":"journal-article","created":{"date-parts":[[2025,4,3]],"date-time":"2025-04-03T20:29:26Z","timestamp":1743712166000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["A Survey of Perceptual Hashing for Multimedia"],"prefix":"10.1145","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4512-8553","authenticated-orcid":false,"given":"Yuanding","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4182-3989","authenticated-orcid":false,"given":"Xinran","family":"Li","sequence":"additional","affiliation":[{"name":"Business School, University of Shanghai for Science and Technology, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6201-2520","authenticated-orcid":false,"given":"Cheng","family":"Xiong","sequence":"additional","affiliation":[{"name":"School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3784-4157","authenticated-orcid":false,"given":"Heng","family":"Yao","sequence":"additional","affiliation":[{"name":"School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0370-4623","authenticated-orcid":false,"given":"Chuan","family":"Qin","sequence":"additional","affiliation":[{"name":"School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China"}]}],"member":"320","published-online":{"date-parts":[[2025,7,19]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3089879"},{"key":"e_1_3_1_3_2","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1109\/ISM55400.2022.00013","volume-title":"Proceedings of 2022 IEEE International Symposium on Multimedia (ISM)","author":"Abbas S.","year":"2022","unstructured":"S. Abbas, S. Jannat, and Y. Chen. 2022. Aggregated bidirectional local binary pattern for robust perceptual image hashing. In Proceedings of 2022 IEEE International Symposium on Multimedia (ISM), 50\u201357."},{"key":"e_1_3_1_4_2","first-page":"1","article-title":"Perceptual hashing-based image copy-move forgery detection","volume":"2018","author":"Wang H.","year":"2018","unstructured":"H. Wang and H. Wang. 2018. Perceptual hashing-based image copy-move forgery detection. Security & Communication Networks 2018 (2018), 1\u201311.","journal-title":"Security & Communication Networks"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2018.2876837"},{"key":"e_1_3_1_6_2","first-page":"371","volume-title":"Proceedings of the 11th International Workshop on Fast Software Encryption","author":"Rogaway P.","unstructured":"P. Rogaway and T. Shrimpton. 2004. Cryptographic hash-function basics: Definitions, implications, and separations for preimage resistance, second-preimage resistance, and collision resistance. In Proceedings of the 11th International Workshop on Fast Software Encryption, 371\u2013388."},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1002\/ett.4978"},{"key":"e_1_3_1_8_2","first-page":"1","volume-title":"Proceedings of the International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC)","author":"Roy M.","year":"2023","unstructured":"M. Roy, D. Thounaojam, and S. Pal. 2023. Various approaches to perceptual image hashing systems\u2014A survey. In Proceedings of the International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC), 1\u20139."},{"issue":"1","key":"e_1_3_1_9_2","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/s11554-023-01269-9","article-title":"Image perceptual hashing for content authentication based on Watson\u2019s visual model and lle","volume":"20","author":"Xing H.","year":"2023","unstructured":"H. Xing, H. Che, Q. Wu, and H. Wang. 2023. Image perceptual hashing for content authentication based on Watson\u2019s visual model and lle. Journal of Real-Time Image Processing 20, 1 (2023), 7.","journal-title":"Journal of Real-Time Image Processing"},{"key":"e_1_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3293609"},{"key":"e_1_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2020.3027001"},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3392763"},{"key":"e_1_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2023.12.018"},{"key":"e_1_3_1_14_2","doi-asserted-by":"crossref","first-page":"121516","DOI":"10.1016\/j.eswa.2023.121516","article-title":"Similarity graph-correlation reconstruction network for unsupervised cross-modal hashing","volume":"237","author":"Yao D.","year":"2024","unstructured":"D. Yao, Z. Li, B. Li, C. Zhang, and H. Ma. 2024. Similarity graph-correlation reconstruction network for unsupervised cross-modal hashing. Expert Systems with Applications 237, Part B (2024), 121516.","journal-title":"Expert Systems with Applications"},{"key":"e_1_3_1_15_2","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.jvcir.2015.07.012","article-title":"Semantic content-based image retrieval: A comprehensive study","volume":"32","author":"Ahmad A.","year":"2015","unstructured":"A. Ahmad, A. Abbes, and R. Naeem. 2015. Semantic content-based image retrieval: A comprehensive study. Journal of Visual Communication and Image Representation 32 (2015), 20\u201354.","journal-title":"Journal of Visual Communication and Image Representation"},{"key":"e_1_3_1_16_2","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1016\/j.future.2023.04.005","article-title":"PIHA: Detection method using perceptual image hashing against query-based adversarial attacks","volume":"145","author":"Choi S.","year":"2023","unstructured":"S. Choi, J. Shin, and Y. Choi. 2023. PIHA: Detection method using perceptual image hashing against query-based adversarial attacks. Future Generation Computer Systems-the International Journal of Escience 145 (2023), 563\u2013577.","journal-title":"Future Generation Computer Systems-the International Journal of Escience"},{"key":"e_1_3_1_17_2","first-page":"142","volume-title":"Proceedings of the 5th International Workshop on Quality of Multimedia Experience (QoMEX)","author":"Jinda-Apiraksa A.","year":"2013","unstructured":"A. Jinda-Apiraksa, V. Vonikakis, and S. Winkler. 2013. California-ND: An annotated dataset for near-duplicate detection in personal photo collections. In Proceedings of the 5th International Workshop on Quality of Multimedia Experience (QoMEX), 142\u2013147."},{"key":"e_1_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11831-020-09400-w"},{"key":"e_1_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2010.2051286"},{"key":"e_1_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.04.036"},{"issue":"9","key":"e_1_3_1_21_2","first-page":"2024","article-title":"SIFT based image hashing algorithm","volume":"32","author":"Liu Z.","year":"2011","unstructured":"Z. Liu, Q. Li, J. Liu, and X. Peng. 2011. SIFT based image hashing algorithm. Chinese Journal of Scientific Instrument 32, 9 (2011), 2024\u20132028.","journal-title":"Chinese Journal of Scientific Instrument"},{"key":"e_1_3_1_22_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2012.2190594"},{"issue":"7","key":"e_1_3_1_23_2","doi-asserted-by":"crossref","first-page":"1336","DOI":"10.1109\/TIFS.2015.2407698","article-title":"A visual model-based perceptual image hash for content authentication","volume":"10","author":"Wang X.","year":"2015","unstructured":"X. Wang, K. Pang, X. Zhou, Y. Zhou, L. Li, and J. Xue. 2015. A visual model-based perceptual image hash for content authentication. IEEE Transactions on Information Forensics & Security 10, 7 (2015), 1336\u20131349.","journal-title":"IEEE Transactions on Information Forensics & Security"},{"key":"e_1_3_1_24_2","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.displa.2016.09.003","article-title":"Perceptual image hashing with selective sampling for salient structure features","volume":"45","author":"Qin C.","year":"2017","unstructured":"C. Qin, X. Chen, J. Dong, and X. Zhang. 2017. Perceptual image hashing with selective sampling for salient structure features. Displays 45 (2017), 26\u201337.","journal-title":"Displays"},{"issue":"6","key":"e_1_3_1_25_2","first-page":"833","article-title":"Robust image hashing based on color vector angle and canny operator","volume":"70","author":"Zhang X.","year":"2016","unstructured":"X. Zhang, Z. Tang, L. Huang, and H. Lao. 2016. Robust image hashing based on color vector angle and canny operator. AEU: Archiv fur Elektronik und Ubertragungstechnik: Electronic and Communication 70, 6 (2016), 833\u2013841.","journal-title":"AEU: Archiv fur Elektronik und Ubertragungstechnik: Electronic and Communication"},{"issue":"3","key":"e_1_3_1_26_2","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1049\/iet-ipr.2013.0332","article-title":"Robust image hashing via colour vector angles and discrete wavelet transform","volume":"8","author":"Huang L.","year":"2014","unstructured":"L. Huang, Z. Tang, F. Yang, Y. Dai, and X. Zhang. 2014. Robust image hashing via colour vector angles and discrete wavelet transform. IET Image Process 8, 3 (2014), 142\u2013149.","journal-title":"IET Image Process"},{"key":"e_1_3_1_27_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijleo.2014.05.015"},{"key":"e_1_3_1_28_2","doi-asserted-by":"publisher","DOI":"10.1145\/3355394"},{"issue":"2","key":"e_1_3_1_29_2","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1179\/1743131X11Y.0000000039","article-title":"Perceptual image hashing using local entropies and DWT","volume":"61","author":"Tang Z.","year":"2013","unstructured":"Z. Tang, X. Zhang, Y. Dai, and W. Lan. 2013. Perceptual image hashing using local entropies and DWT. Imaging Science Journal 61, 2 (2013), 241\u2013251.","journal-title":"Imaging Science Journal"},{"key":"e_1_3_1_30_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2012.11.002"},{"key":"e_1_3_1_31_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2013.01.008"},{"key":"e_1_3_1_32_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2015.2485163"},{"key":"e_1_3_1_33_2","doi-asserted-by":"crossref","first-page":"107244.1\u2013107244","DOI":"10.1016\/j.sigpro.2019.107244","article-title":"Perceptual hashing for color image based on color opponent component and quadtree structure","volume":"166","author":"Shen Q.","year":"2020","unstructured":"Q. Shen and Y. Zhao. 2020. Perceptual hashing for color image based on color opponent component and quadtree structure. Signal Processing 166 (Jan. 2020), 107244.1\u2013107244.12.","journal-title":"Signal Processing"},{"key":"e_1_3_1_34_2","first-page":"1","volume-title":"Proceedings of the International Conference on Information Technology & Electrical Engineering","author":"Setyawan I.","year":"2014","unstructured":"I. Setyawan and I. Timotius. 2014. Digital image hashing using local histogram of oriented gradients. In Proceedings of the International Conference on Information Technology & Electrical Engineering, 1\u20134."},{"key":"e_1_3_1_35_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2024.3405660"},{"key":"e_1_3_1_36_2","doi-asserted-by":"crossref","first-page":"103578","DOI":"10.1016\/j.jisa.2023.103578","article-title":"Robust image hashing based on multi-view dimension reduction","volume":"77","author":"Du L.","year":"2023","unstructured":"L. Du, Q. Shang, Z. Wang, and X. Wang. 2023. Robust image hashing based on multi-view dimension reduction. Journal of Information Security and Applications 77 (2023), 103578.","journal-title":"Journal of Information Security and Applications"},{"key":"e_1_3_1_37_2","first-page":"3443","volume-title":"Proceedings of the International Conference on Image Processing","volume":"5","author":"Kozat S.","year":"2004","unstructured":"S. Kozat, R. Venkatesan, and M. Mihcak. 2004. Robust perceptual image hashing via matrix invariants. In Proceedings of the International Conference on Image Processing, Vol. 5, 3443\u20133446."},{"key":"e_1_3_1_38_2","first-page":"401","volume-title":"Proceedings of the 8th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)","author":"Abbas S.","year":"2016","unstructured":"S. Abbas, F. Ahmed, N. Zivic, and O. Ur-Rehman. 2016. Perceptual image hashing using SVD based noise resistant local binary pattern. In Proceedings of the 8th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), 401\u2013407."},{"key":"e_1_3_1_39_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.45"},{"key":"e_1_3_1_40_2","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.dsp.2015.05.002","article-title":"Robust image hashing with embedding vector variance of lle","volume":"43","author":"Ruan L.","year":"2015","unstructured":"L. Ruan, Z. Tang, X. Zhang, C. Yu, and C. Qin. 2015. Robust image hashing with embedding vector variance of lle. Digital Signal Processing 43 (2015), 17\u201327.","journal-title":"Digital Signal Processing"},{"key":"e_1_3_1_41_2","first-page":"1285","volume-title":"Proceedings of the IEEE International Conference on Image Processing","author":"Kang L.","year":"2009","unstructured":"L. Kang, C. Lu, and C. Hsu. 2009. Compressive sensing-based image hashing. In Proceedings of the IEEE International Conference on Image Processing, 1285\u20131288."},{"key":"e_1_3_1_42_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2019.2890966"},{"key":"e_1_3_1_43_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2020.3047142"},{"key":"e_1_3_1_44_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-021-05956-1"},{"key":"e_1_3_1_45_2","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2024.3353057"},{"key":"e_1_3_1_46_2","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1145\/3577163.3595113","volume-title":"Proceedings of ACM Workshop on Information Hiding and Multimedia Security (IH&MMSec \u201923)","author":"Fang Y.","year":"2023","unstructured":"Y. Fang, Y. Zhou, X. Li, P. Kong, and C. Qin. 2023. TMCIH: Perceptual robust image hashing with transformer-based multi-layer constraints. In Proceedings of ACM Workshop on Information Hiding and Multimedia Security (IH&MMSec \u201923), 7\u201312."},{"key":"e_1_3_1_47_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3221980"},{"key":"e_1_3_1_48_2","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3612457"},{"issue":"12","key":"e_1_3_1_49_2","first-page":"2551","article-title":"A bidirectional generative adversarial network-based perceptual hash algorithm for image content forensics","volume":"46","author":"Ma B.","year":"2023","unstructured":"B. Ma, Y. Wang, J. Xu, C. Wang, J. Li, L. Zhou, and Y. Shi. 2023. A bidirectional generative adversarial network-based perceptual hash algorithm for image content forensics. Chiness Journal of Computers 46, 12 (2023), 2551\u20132572.","journal-title":"Chiness Journal of Computers"},{"issue":"1","key":"e_1_3_1_50_2","first-page":"4235268","article-title":"Image hashing for tamper detection with multiview embedding and perceptual saliency","volume":"2018","author":"Du Ling","year":"2018","unstructured":"Ling Du, Zhen Chen, and Yongzhen Ke. 2018. Image hashing for tamper detection with multiview embedding and perceptual saliency. Advances in Multimedia 2018, 1 (2018), 4235268.","journal-title":"Advances in Multimedia"},{"key":"e_1_3_1_51_2","first-page":"1645658","volume-title":"Wireless Communications and Mobile Computing","author":"Shaik A.","year":"2022","unstructured":"A. Shaik, R. Karsh, M. Islam, and S. Singh. 2022. A secure and robust autoencoder-based perceptual image hashing for image authentication. Wireless Communications and Mobile Computing 2022, 1 (2022), 1645658."},{"key":"e_1_3_1_52_2","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.neunet.2022.09.028","article-title":"Robust image hashing for content identification through contrastive self-supervised learning","volume":"156","author":"Jesus F.","year":"2022","unstructured":"F. Jesus, A. Kelsey, and F. Claudia. 2022. Robust image hashing for content identification through contrastive self-supervised learning. Neural Networks 156 (2022), 81\u201394.","journal-title":"Neural Networks"},{"issue":"1","key":"e_1_3_1_53_2","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1080\/13682199.2016.1260216","article-title":"Collusion and rotation resilient video hashing based on scale invariant feature transform","volume":"65","author":"Neelima A.","year":"2017","unstructured":"A. Neelima and K. M. Singh. 2017. Collusion and rotation resilient video hashing based on scale invariant feature transform. The Imaging Science Journal 65, 1 (2017), 62\u201374.","journal-title":"The Imaging Science Journal"},{"issue":"1","key":"e_1_3_1_54_2","first-page":"33","article-title":"A robust hashing algorithm based on surf for video copy detection","volume":"31","author":"Yang G.","year":"2012","unstructured":"G. Yang, N. Chen, and Q. Jiang. 2012. A robust hashing algorithm based on surf for video copy detection. Elsevier Advanced Technology Publications 31, 1 (2012), 33\u201339.","journal-title":"Elsevier Advanced Technology Publications"},{"key":"e_1_3_1_55_2","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.ijleo.2016.09.105","article-title":"Robust video fingerprinting scheme based on contourlet hidden Markov tree model","volume":"128","author":"Sun R.","year":"2017","unstructured":"R. Sun, X. Yan, and J. Gao. 2017. Robust video fingerprinting scheme based on contourlet hidden Markov tree model. Optik 128 (2017), 139\u2013147.","journal-title":"Optik"},{"key":"e_1_3_1_56_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2008.920739"},{"key":"e_1_3_1_57_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2005.855414"},{"key":"e_1_3_1_58_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.09.001"},{"key":"e_1_3_1_59_2","first-page":"2648","volume-title":"IEEE Internet of Things Journal","volume":"11","author":"Chen L.","year":"2024","unstructured":"L. Chen, D. Ye, and Y. Shang. 2024. Perceptual video hashing with secure anti-noise model for social video retrieval. IEEE Internet of Things Journal. 11, 2 (2024), 2648\u20132664."},{"key":"e_1_3_1_60_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00530-014-0447-0"},{"key":"e_1_3_1_61_2","doi-asserted-by":"publisher","DOI":"10.4236\/jsip.2016.72010"},{"key":"e_1_3_1_62_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-019-7513-8"},{"key":"e_1_3_1_63_2","first-page":"233","volume-title":"Proceedings of the IEEE 2nd International Conference on Multimedia Big Data (BigMM)","author":"Ren D.","year":"2016","unstructured":"D. Ren, L. Zhuo, H. Long, P. Qu, and J. Zhang. 2016. MPEG2 video copy detection method based on sparse representation of spatial and temporal features. In Proceedings of the IEEE 2nd International Conference on Multimedia Big Data (BigMM), 233\u2013236."},{"key":"e_1_3_1_64_2","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2016.2530714"},{"key":"e_1_3_1_65_2","first-page":"347","volume-title":"Proceedings of the IEEE International Conference on Computer Vision Workshops (ICCV Workshops \u201917)","author":"Giorgos K.","year":"2017","unstructured":"K. Giorgos, P. Symeon, P. Ioannis, and K. Yiannis. 2017. Near-duplicate video retrieval with deep metric learning. In Proceedings of the IEEE International Conference on Computer Vision Workshops (ICCV Workshops \u201917), 347\u2013356."},{"key":"e_1_3_1_66_2","first-page":"2162","volume-title":"Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP \u201917)","author":"Li Y.","year":"2017","unstructured":"Y. Li and X. Chen. 2017. Robust and compact video descriptor learned by deep neural network. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP \u201917), 2162\u20132166."},{"key":"e_1_3_1_67_2","doi-asserted-by":"publisher","DOI":"10.1109\/TAI.2023.3318888"},{"key":"e_1_3_1_68_2","doi-asserted-by":"crossref","unstructured":"J. Song H. Zhang X. Li L. Gao M. Wang and R. Hong. 2018. Self-supervised video hashing with hierarchical binary auto-encoder. IEEE Transactions on Image Processing 27 7 (2018) 3210\u20133221.","DOI":"10.1109\/TIP.2018.2814344"},{"key":"e_1_3_1_69_2","doi-asserted-by":"publisher","DOI":"10.1145\/3577163.3595110"},{"key":"e_1_3_1_70_2","first-page":"123:1","volume-title":"ACM Transactions on Multimedia Computing, Communications, and Applications","volume":"19","author":"Chen H.","year":"2023","unstructured":"H. Chen, H. Zhou, J. Zhang, D. Chen, W. Zhang, K. Chen, G. Hua, and N. Yu. 2023. Perceptual hashing of deep convolutional neural networks for model copy detection. ACM Transactions on Multimedia Computing, Communications, and Applications 19, 3 (2023), 123:1\u2013123:20."},{"key":"e_1_3_1_71_2","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3548247"},{"key":"e_1_3_1_72_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2019.12.016"},{"key":"e_1_3_1_73_2","doi-asserted-by":"publisher","DOI":"10.3390\/sym14040810"},{"issue":"12","key":"e_1_3_1_74_2","doi-asserted-by":"crossref","first-page":"1378","DOI":"10.1002\/sec.265","article-title":"Content based image hashing using companding and gray code","volume":"4","author":"Lei Y.","year":"2011","unstructured":"Y. Lei, C. Qian, J. Tian, and D. Wu. 2011. Content based image hashing using companding and gray code. Security & Communication Networks 4, 12 (2011), 1378\u20131386.","journal-title":"Security & Communication Networks"},{"issue":"1","key":"e_1_3_1_75_2","first-page":"87","article-title":"Image matching algorithm based on kaze and perceptual hash","volume":"42","author":"Xu M.","year":"2021","unstructured":"M. Xu, W. Liu, C. Cai, and X. Zheng. 2021. Image matching algorithm based on kaze and perceptual hash. Chinese Journal of Semiconductor Optoelectronics 42, 1 (2021), 87\u201392.","journal-title":"Chinese Journal of Semiconductor Optoelectronics"},{"key":"e_1_3_1_76_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1986.4767851"},{"key":"e_1_3_1_77_2","first-page":"401","volume-title":"Proceedings of the 8th International Conference for Internet Technology and Secured Transactions (ICITST \u201913)","author":"Prungsinchai S.","year":"2013","unstructured":"S. Prungsinchai, F. Khelifi, and A. Bouridane. 2013. DCT sign-based robust image hashing. In Proceedings of the 8th International Conference for Internet Technology and Secured Transactions (ICITST \u201913), 401\u2013405."},{"key":"e_1_3_1_78_2","doi-asserted-by":"publisher","DOI":"10.1006\/jvci.2001.0487"},{"key":"e_1_3_1_79_2","doi-asserted-by":"crossref","first-page":"106357","DOI":"10.1016\/j.neunet.2024.106357","article-title":"A robust self-supervised image hashing method for content identification with forensic detection of content-preserving manipulations","volume":"177","author":"Jesus F.","year":"2024","unstructured":"F. Jesus, R. Kelsey, and F. Claudia. 2024. A robust self-supervised image hashing method for content identification with forensic detection of content-preserving manipulations. Neural Networks 177 (2024), 106357.","journal-title":"Neural Networks"},{"key":"e_1_3_1_80_2","first-page":"95","volume-title":"Proceedings of 22nd International Workshop on Digital Watermarking","author":"Yang M.","year":"2023","unstructured":"M. Yang, B. Qi, and Y. Xian ang, J. Li. 2023. An image perceptual hashing algorithm based on convolutional neural networks. In Proceedings of 22nd International Workshop on Digital Watermarking, 95\u2013108."},{"key":"e_1_3_1_81_2","doi-asserted-by":"publisher","DOI":"10.1109\/MMUL.2024.3354998"},{"key":"e_1_3_1_82_2","doi-asserted-by":"publisher","DOI":"10.1093\/comjnl\/bxad130"},{"key":"e_1_3_1_83_2","volume-title":"Modern Information Retrieval\u2014The Concepts and Technology Behind Search","author":"Yates R.","year":"2011","unstructured":"R. Yates and B. RibeiroNeto. 2011. Modern Information Retrieval\u2014The Concepts and Technology Behind Search (2nd ed.). Addison-Wesley Professional.","edition":"2"},{"key":"e_1_3_1_84_2","first-page":"1345","volume-title":"Proceedings of the Advances in Neural Information Processing Systems 19, Proceedings of the 20th Annual Conference on Neural Information Processing Systems","author":"Taylor G.","year":"2006","unstructured":"G. Taylor, G. Hinton, and S. Roweis. 2006. Modeling human motion using binary latent variables. In Proceedings of the Advances in Neural Information Processing Systems 19, Proceedings of the 20th Annual Conference on Neural Information Processing Systems, 1345\u20131352."},{"key":"e_1_3_1_85_2","first-page":"548","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV \u201921)","author":"Wang W.","year":"2021","unstructured":"W. Wang, E. Xie, X. Li, D. Fan, K. Song, D. Liang, T. Lu, P. Luo, and L. Shao. 2021. Pyramid vision transformer: A versatile backbone for dense prediction without convolutions. In Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV \u201921), 548\u2013558."},{"key":"e_1_3_1_86_2","first-page":"740","volume-title":"Proceedings of the 13th European Conference","author":"Lin T.","year":"2014","unstructured":"T. Lin, M. Maire, S. Belongie, J. Hays, and C. Zitnick. 2014. Microsoft COCO: Common objects in context. In Proceedings of the 13th European Conference, Vol. 8693, 740\u2013755."},{"key":"e_1_3_1_87_2","first-page":"422","volume-title":"Proceedings of the IEEE China Summit and International Conference on Signal and Information Processing","author":"Jing D.","year":"2013","unstructured":"D. Jing, W. Wei, and T. Tan. 2013. Casia image tampering detection evaluation database. In Proceedings of the IEEE China Summit and International Conference on Signal and Information Processing, 422\u2013426."},{"key":"e_1_3_1_88_2","volume-title":"Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR \u201909)","author":"Deng J.","year":"2009","unstructured":"J. Deng, W. Dong, R. Socher, L. Li, and F. Li. 2009. ImageNet: A large-scale hierarchical image database. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR \u201909)."},{"key":"e_1_3_1_89_2","doi-asserted-by":"publisher","DOI":"10.1145\/2713168.2713194"},{"key":"e_1_3_1_90_2","first-page":"472","article-title":"UCID: An uncompressed color image database","volume":"5307","author":"Schaefer G.","year":"2004","unstructured":"G. Schaefer and M. Stich. 2004. UCID: An uncompressed color image database. In Proceedings of the SPIE Storage and Retrieval Methods and Applications for Multimedia, Vol. 5307, 472\u2013480.","journal-title":"In Proceedings of the SPIE Storage and Retrieval Methods and Applications for Multimedia"},{"key":"e_1_3_1_91_2","volume-title":"Usc Sipi Image Database USC SIPI Report","author":"Weber. 1997 A.","unstructured":"A. Weber. 1997. USC-SIPI Image Database Version 5. Usc Sipi Image Database USC SIPI Report."},{"key":"e_1_3_1_92_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-014-0733-5"},{"issue":"19","key":"e_1_3_1_93_2","doi-asserted-by":"crossref","first-page":"5582","DOI":"10.1016\/j.ijleo.2014.07.006","article-title":"Robust image hashing using invariants of tchebichef moments","volume":"125","author":"Chen Y.","year":"2014","unstructured":"Y. Chen, W. Yu, and J. Feng. 2014. Robust image hashing using invariants of tchebichef moments. Optik-International Journal for Light and Electron Optics 125, 19 (2014), 5582\u20135587.","journal-title":"Optik-International Journal for Light and Electron Optics"},{"key":"e_1_3_1_94_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.2971142"}],"container-title":["ACM Transactions on Multimedia Computing, Communications, and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3727880","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,19]],"date-time":"2025-07-19T11:15:53Z","timestamp":1752923753000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3727880"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,19]]},"references-count":93,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2025,7,31]]}},"alternative-id":["10.1145\/3727880"],"URL":"https:\/\/doi.org\/10.1145\/3727880","relation":{},"ISSN":["1551-6857","1551-6865"],"issn-type":[{"value":"1551-6857","type":"print"},{"value":"1551-6865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,19]]},"assertion":[{"value":"2024-08-31","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-03-28","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-19","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}