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

Baig, Asim, Al-Maadeed, Somaya, Bouridane, Ahmed and Cheriet, Mohamed (2016) Direct unsupervised text line extraction from colored historical manuscript images using DCT. In: Image Analysis and Recognition: Proceedings of the 13th International Conference, ICIAR 2016, in Memory of Mohamed Kamel. Lecture notes in computer science, 9730 . Springer, London, pp. 753-762. ISBN 9783319415000

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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.

Item Type: Book Section
Uncontrolled Keywords: text line extraction, segmentation, DCT, Historical manuscripts, color image processing
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 08 Aug 2016 14:21
Last Modified: 10 Nov 2016 12:40

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