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

被引：0

作者：

Baig, Asim ^{[1
]}

Al-Maadeed, Somaya ^{[1
]}

Bouridane, Ahmed ^{[2
]}

Cheriet, Mohamed ^{[3
]}

机构：

[1] Qatar Univ, Doha, Qatar

[2] Northumbria Univ, Newcastle Upon Tyne, Tyne & Wear, England

[3] Ecole Technol Super, Montreal, PQ, Canada

来源：

IMAGE ANALYSIS AND RECOGNITION (ICIAR 2016) | 2016年 / 9730卷

关键词：

Text line extraction; Segmentation; DCT; Historical manuscripts; Color image processing;

D O I：

10.1007/978-3-319-41501-7_84

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：753 / 762

页数：10

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