期刊
IMAGE AND VISION COMPUTING
卷 28, 期 4, 页码 590-604出版社
ELSEVIER
DOI: 10.1016/j.imavis.2009.09.013
关键词
Text line segmentation; Word segmentation; Character segmentation; Historical machine-printed documents; Run Length Smoothing Algorithm
类别
资金
- European Community's Seventh Framework Programme [215064]
- Greek Ministry of Research
In this paper, we strive towards the development of efficient techniques in order to segment document pages resulting from the digitization of historical machine-printed sources. This kind of documents often suffer from low quality and local skew, several degradations due to the old printing matrix quality or ink diffusion, and exhibit complex and dense layout. To face these problems, we introduce the following innovative aspects: (i) use of a novel Adaptive Run Length Smoothing Algorithm (ARLSA) in order to face the problem of complex and dense document layout, (ii) detection of noisy areas and punctuation marks that are usual in historical machine-printed documents, (iii) detection of possible obstacles formed from background areas in order to separate neighboring text columns or text lines, and (iv) use of skeleton segmentation paths in order to isolate possible connected characters. Comparative experiments using several historical machine-printed documents prove the efficiency of the proposed technique. (C) 2009 Elsevier B.V. All rights reserved.
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