{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T21:37:07Z","timestamp":1775770627853,"version":"3.50.1"},"reference-count":138,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,4,26]],"date-time":"2025-04-26T00:00:00Z","timestamp":1745625600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Umm Al-Qura University, Saudi Arabia","award":["25UQU4361170GSSR01"],"award-info":[{"award-number":["25UQU4361170GSSR01"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>In today\u2019s digital age, the conversion of hardcopy documents into digital formats is widespread. This process involves electronically scanning and storing large volumes of documents. These documents come from various sources, including records and reports, camera-captured text and screen snapshots, official documents, newspapers, medical reports, music scores, and more. In the domain of document analysis techniques, an essential step is document image binarization. Its goal is to eliminate unnecessary data from images and preserve only the text. Despite the existence of multiple techniques for binarization, the presence of degradation in document images can hinder their efficacy. The objective of this work is to provide an extensive review and analysis of the document binarization field, emphasizing its importance and addressing the challenges encountered during the image binarization process. Additionally, it provides insights into techniques and methods employed for image binarization. The current paper also introduces benchmark datasets for evaluating binarization accuracy, model training, evaluation metrics, and the effectiveness of recent methods.<\/jats:p>","DOI":"10.3390\/jimaging11050133","type":"journal-article","created":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T04:25:50Z","timestamp":1745814350000},"page":"133","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["A Comprehensive Review on Document Image Binarization"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4525-1642","authenticated-orcid":false,"given":"Bilal","family":"Bataineh","sequence":"first","affiliation":[{"name":"Software Engineering Department, Faculty of Science and Information Technology, Irbid National University, Irbid 21110, Jordan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1299-9005","authenticated-orcid":false,"given":"Mohamed","family":"Tounsi","sequence":"additional","affiliation":[{"name":"Software Engineering Department, College of Computing, Umm Al-Qura University, Mecca 21955, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9328-9218","authenticated-orcid":false,"given":"Nuha","family":"Zamzami","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, Jeddah 21959, Saudi Arabia"}]},{"given":"Jehan","family":"Janbi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, College of Computer and Information Technology, Taif University, Taif 21944, Saudi Arabia"}]},{"given":"Waleed Abdel Karim","family":"Abu-ain","sequence":"additional","affiliation":[{"name":"Applied College, Taibah University, Madinah 41477, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8023-7600","authenticated-orcid":false,"given":"Tarik","family":"AbuAin","sequence":"additional","affiliation":[{"name":"College of Computing and Informatics, Saudi Electronic University, Riyadh 11673, Saudi Arabia"}]},{"given":"Shaima","family":"Elnazer","sequence":"additional","affiliation":[{"name":"Communication and Electronic Department, Nile Academy for Science and Technology, El Mansoura 35516, Egypt"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5470","DOI":"10.1016\/j.eswa.2011.11.078","article-title":"A novel statistical feature extraction method for textual images: Optical font recognition","volume":"39","author":"Bataineh","year":"2012","journal-title":"Expert Syst. 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