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المؤلفBaig, Asim
المؤلفAl-Maadeed, Somaya
المؤلفBouridane, Ahmed
المؤلفCheriet, Mohamed
تاريخ الإتاحة2021-09-07T06:16:17Z
تاريخ النشر2016
اسم المنشورLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
المصدرScopus
الرقم المعياري الدولي للكتاب3029743
معرّف المصادر الموحدhttp://dx.doi.org/10.1007/978-3-319-41501-7_84
معرّف المصادر الموحدhttp://hdl.handle.net/10576/22791
الملخصExtracting lines of text from a manuscript is an important preprocessing step in many digital paleography applications. These extracted lines play a fundamental part in the identification of the author and/or age of the manuscript. In this paper we present an unsupervised approach to text line extraction in historical manuscripts that can be applied directly to a color manuscript image. Each of the red, green and blue channels are processed separately by applying DCT on them individually. One of the key advantages of this approach is that it can be applied directly to the manuscript image without any preprocessing, training or tuning steps. Extensive testing on complex Arabic handwritten manuscripts shows the effectiveness of the proposed approach. Springer International Publishing Switzerland 2016.
اللغةen
الناشرSpringer Verlag
الموضوعColor image processing
DCT
Historical manuscripts
Segmentation
Text line extraction
العنوانDirect unsupervised text line extraction from colored historical manuscript images using DCT
النوعConference Paper
الصفحات753-762
رقم المجلد9730
dc.accessType Abstract Only


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