Writer identification on historical Glagolitic documents

Fiel, Stefan; Hollaus, Fabian; Gau, Melanie; Sablatnig, Robert

doi:10.1117/12.2042338

Cited by 3 publications

(1 citation statement)

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“…Automatic detection of text lines in these documents can be of great benefit to them. Automatic text line detection is considered to be a key preprocessing step in many digital paleographic applications such as Content Based Image Retrieval (CBIR) [1], manuscript author identification [2] and manuscripts age detection [3] to name a few. Reliable and quick extraction of text lines can improve the accuracy of these applications.…”

Section: Introductionmentioning

confidence: 99%

Direct Unsupervised Text Line Extraction from Colored Historical Manuscript Images Using DCT

Baig

Al-Maadeed

Bouridane

et al. 2016

Lecture Notes in Computer Science

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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.

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Section: Introductionmentioning

confidence: 99%