{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:59:58Z","timestamp":1760241598271,"version":"build-2065373602"},"reference-count":25,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2018,6,12]],"date-time":"2018-06-12T00:00:00Z","timestamp":1528761600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Slanted text has been demonstrated to be a salient feature of handwriting. Its estimation is a necessary preprocessing task in many document image processing systems in order to improve the required training. This paper describes and evaluates a new technique for removing the slant from historical document pages that avoids the segmentation procedure into text lines and words. The proposed technique first relies on slant angle detection from an accurate selection of fragments. Then, a slant removal technique is applied. However, the presented slant removal technique may be combined with any other slant detection algorithm. Experimental results are provided for four document image databases: two historical document databases, the TrigraphSlant database (the only database dedicated to slant removal), and a printed database in order to check the precision of the proposed technique.<\/jats:p>","DOI":"10.3390\/jimaging4060080","type":"journal-article","created":{"date-parts":[[2018,6,12]],"date-time":"2018-06-12T10:58:32Z","timestamp":1528801112000},"page":"80","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Slant Removal Technique for Historical Document Images"],"prefix":"10.3390","volume":"4","author":[{"given":"Ergina","family":"Kavallieratou","sequence":"first","affiliation":[{"name":"Department Information and Communication Systems Engineering, University of the Aegean, Samos 83200, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laurence","family":"Likforman-Sulem","sequence":"additional","affiliation":[{"name":"Institut Mines-T\u00e9l\u00e9com\/T\u00e9l\u00e9com ParisTech, Universit\u00e9 Paris-Saclay, 75013 Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nikos","family":"Vasilopoulos","sequence":"additional","affiliation":[{"name":"Department Information and Communication Systems Engineering, University of the Aegean, Samos 83200, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,6,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.patcog.2012.07.012","article-title":"Arabic handwriting recognition using structural and syntactic pattern attributes","volume":"46","author":"Parvez","year":"2013","journal-title":"Pattern Recognit."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2106","DOI":"10.1016\/j.patcog.2009.02.005","article-title":"Handwritten word-spotting using hidden Markov models and universal vocabularies","volume":"42","author":"Perronnin","year":"2009","journal-title":"Pattern Recognit."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1016\/j.patrec.2010.10.010","article-title":"Towards robust writer verification by correcting unnatural slant","volume":"32","author":"Brink","year":"2011","journal-title":"Pattern Recognit. 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