Direct unsupervised text line extraction from colored historical manuscript images using DCT

Asim Baig, Somaya Al-Maadeed, Ahmed Bouridane, Mohamed Cheriet

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Extracting 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.
Original languageEnglish
Title of host publicationImage Analysis and Recognition: Proceedings of the 13th International Conference, ICIAR 2016, in Memory of Mohamed Kamel
EditorsAurélio Campilho, Fakhri Karray
Place of PublicationLondon
PublisherSpringer
Pages753-762
Volume9730
ISBN (Print)9783319415000
DOIs
Publication statusPublished - 2016

Publication series

NameLecture notes in computer science
PublisherSpringer
ISSN (Electronic)0302-9743

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