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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/92967

    Title: A machine-learning approach for analyzing document layout structures with two reading orders
    Authors: Wu, Chung-Chih;Chou, Chien-Hsing;Chang, Fu
    Contributors: 淡江大學電機工程學系
    Keywords: Binary decision;Document layout analysis;Reading order;Support vector machine;Taboo box;Textline;Text region
    Date: 2008-10
    Issue Date: 2013-10-29 15:30:49 (UTC+8)
    Publisher: Kidlington: Pergamon
    Abstract: The purpose of document layout analysis is to locate textlines and text regions in document images mostly via a series of split-or-merge operations. Before applying such an operation, however, it is necessary to examine the context to decide whether the place chosen for the operation is appropriate. We thus view document layout analysis as a matter of solving a series of binary decision problems, such as whether to apply, or not to apply, a split-or-merge operation to a chosen place. To solve these problems, we use support vector machines to learn whether or not to apply the previously mentioned operations from training documents in which all textlines and text regions have been located and their identifies labeled. The proposed approach is very effective for analyzing documents that allow both horizontal and vertical reading orders. When applied to a test data set composed of eight types of layout structure, the approach's accuracy rates for identifying textlines and text regions are 98.83% and 96.72%, respectively.
    Relation: Pattern Recognition 41(10), pp.3200-3213
    DOI: 10.1016/j.patcog.2008.03.014
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Journal Article

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