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Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/578187
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dc.contributor.authorSitti Rachmawati Yahya (UKM)
dc.contributor.authorKhairuddin Omar (UKM)
dc.contributor.authorSiti Norul Huda Sheikh Abdullah (UKM)
dc.contributor.authorChoong-Yeun Liong (UKM)
dc.date.accessioned2023-11-06T02:59:02Z-
dc.date.available2023-11-06T02:59:02Z-
dc.date.issued2017-06
dc.identifier.issn0128-7680
dc.identifier.otherukmvital:113371
dc.identifier.urihttps://ptsldigital.ukm.my/jspui/handle/123456789/578187-
dc.descriptionIn this paper, an image binarization method for separating text from the background of degraded textual images is proposed. This proposed methods are based on combination of Window Tracking Method (WTM) and Dynamic Image Histogram (DIH). The WTM and DIH methods work on an image that has been pre-processed. The WTM method searches for the largest pixel value in a 3 × 3 window up to a maximum of five tracking steps, while the method searches for a definite frequency between the two highest values in the image histogram. We test proposed method on DIBCO dataset and self-collection faded manuscripts. The experimental results show that our proposed method outperforms state of the art methods.
dc.language.isoen
dc.publisherUniversiti Putra Malaysia Press
dc.relation.haspartPertanika Journals
dc.relation.urihttp://www.pertanika.upm.edu.my/view_archives.php?journal=JST-25-S-6
dc.rightsUKM
dc.subjectDynamic image histogram
dc.subjectImage smoothness
dc.subjectReference image
dc.subjectStandard deviation
dc.subjectWindow tracking
dc.titleBinarization via the dynamic histogram and window tracking for degraded textual images
dc.typeJournal Article
dc.format.volume25
dc.format.pages63-72
dc.format.issueSpecial Issue
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