{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:25:14Z","timestamp":1760059514509,"version":"build-2065373602"},"reference-count":40,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:00:00Z","timestamp":1750291200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Umm Al-Qura University, Saudi Arabia","award":["25UQU4300346GSSR09"],"award-info":[{"award-number":["25UQU4300346GSSR09"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Identifying the scriptwriter in historical manuscripts is crucial for historians, providing valuable insights into historical contexts and aiding in solving historical mysteries. This research presents a robust deep learning system designed for classifying historical manuscripts by writer, employing intelligent feature selection and vision transformers. Our methodology meticulously investigates the efficacy of both handcrafted techniques for feature identification and deep learning architectures for classification tasks in writer identification. The initial preprocessing phase involves thorough document refinement using bilateral filtering for denoising and Otsu thresholding for binarization, ensuring document clarity and consistency for subsequent feature detection. We utilize the FAST detector for feature detection, extracting keypoints representing handwriting styles, followed by clustering with the k-means algorithm to obtain meaningful patches of uniform size. This strategic clustering minimizes redundancy and creates a comprehensive dataset ideal for deep learning classification tasks. Leveraging vision transformer models, our methodology effectively learns complex patterns and features from extracted patches, enabling precise identification of writers across historical manuscripts. This study pioneers the application of vision transformers in historical document analysis, showcasing superior performance on the \u201cICDAR 2017\u201d dataset compared to state-of-the-art methods and affirming our approach as a robust tool for historical manuscript analysis.<\/jats:p>","DOI":"10.3390\/jimaging11060204","type":"journal-article","created":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T06:11:07Z","timestamp":1750313467000},"page":"204","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Historical Manuscripts Analysis: A Deep Learning System for Writer Identification Using Intelligent Feature Selection with Vision Transformers"],"prefix":"10.3390","volume":"11","author":[{"given":"Merouane","family":"Boudraa","sequence":"first","affiliation":[{"name":"Laboratory of Mathematics, Informatics and Systems (LAMIS), Echahid Cheikh Larbi Tebessi University, Tebessa 12000, Algeria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3185-8806","authenticated-orcid":false,"given":"Akram","family":"Bennour","sequence":"additional","affiliation":[{"name":"Laboratory of Mathematics, Informatics and Systems (LAMIS), Echahid Cheikh Larbi Tebessi University, Tebessa 12000, Algeria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1520-4431","authenticated-orcid":false,"given":"Mouaaz","family":"Nahas","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Umm Al-Qura University, Makkah 21955, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rashiq Rafiq","family":"Marie","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Taibah University, Medina 41477, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7172-8224","authenticated-orcid":false,"given":"Mohammed","family":"Al-Sarem","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Taibah University, Medina 41477, Saudi Arabia"},{"name":"Department of Information Technology, Aylol University College, Yarim 547, Yemen"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3853","DOI":"10.1016\/j.patcog.2010.05.019","article-title":"Text independent writer recognition using redundant writing patterns with contour-based orientation and curvature features","volume":"43","author":"Siddiqi","year":"2010","journal-title":"Pattern Recognit."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1016\/j.imavis.2013.03.002","article-title":"Offline Text-Independent Writer Identification Using Codebook and Efficient Code Extraction Methods","volume":"31","author":"Ghiasi","year":"2013","journal-title":"Image Vis. 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