{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:08:49Z","timestamp":1760148529491,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,5,15]],"date-time":"2023-05-15T00:00:00Z","timestamp":1684108800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Special Funds of Heilongjiang University of the Fundamental Research Funds for the Heilongjiang Province","award":["2021-FYYWF-0015"],"award-info":[{"award-number":["2021-FYYWF-0015"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>This paper proposes a new image hashing method, which uses histogram reconstruction to solve the problem of the histogram not being sensitive to the change of pixel position, while ensuring the robustness of the hashing algorithm against common content preservation attacks (such as blurring, noise addition and rotation). The proposed algorithm can resist arbitrary angles of rotation, possibly because the reconstructed histogram leverages the rotational symmetry and its own invariance to rotation operations. We measure the similarity between different images by calculating the Hamming distance of the hash vectors of different images. Our experiments show that the proposed method performs well in robustness and discrimination compared with other established algorithms. In addition, we conduct a receiver operating characteristic curve analysis to further verify the superior overall performance of our image hash method.<\/jats:p>","DOI":"10.3390\/sym15051088","type":"journal-article","created":{"date-parts":[[2023,5,16]],"date-time":"2023-05-16T02:20:13Z","timestamp":1684203613000},"page":"1088","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Robust Image Hashing Using Histogram Reconstruction for Improving Content Preservation Resistance and Discrimination"],"prefix":"10.3390","volume":"15","author":[{"given":"Yao","family":"Jia","sequence":"first","affiliation":[{"name":"School of Data Science and Technology, Heilongjiang University, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chen","family":"Cui","sequence":"additional","affiliation":[{"name":"School of Data Science and Technology, Heilongjiang University, Harbin 150080, China"},{"name":"College of Mathematics Physics and Information Engineering, Jiaxing University, Jiaxing 314001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5068-2033","authenticated-orcid":false,"given":"Ahmed A. Abd","family":"El-Latif","sequence":"additional","affiliation":[{"name":"EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia"},{"name":"Department of Mathematics and Computer Science, Faculty of Science, Menoufia University, Shebin EI-Koom 32511, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1456","DOI":"10.1016\/j.sigpro.2009.05.024","article-title":"A secure and robust hash-based scheme for image authentication","volume":"90","author":"Ahmed","year":"2010","journal-title":"Signal Process."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1109\/TIFS.2012.2223680","article-title":"Robust hashing for image authentication using Zernike moments and local features","volume":"8","author":"Zhao","year":"2012","journal-title":"IEEE Trans. Inf. 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