Identifying and understanding tabular material in compound documents

Q4 Computer Science 模式识别与人工智能 Pub Date : 1992-08-30 DOI:10.1109/ICPR.1992.201803
A. Laurentini, P. Viada
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引用次数: 50

Abstract

Tables are important components of technical documents. This paper addresses the following problems: (i) identifying a tabular component in a scanned image of a compound document containing text, drawings, diagrams, etc.; (ii) understanding the content of the table in order to convert the table into electronic format. As far as the authors are aware, the problems addressed are new. An algorithm for performing both the above tasks has been studied and implemented. Preliminary experimental results indicate satisfactory performance for many table lay-out styles.<>
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识别和理解复合文档中的表格材料
表格是技术文档的重要组成部分。本文解决以下问题:(i)在包含文本、图纸、图表等的复合文档的扫描图像中识别表格组件;(ii)了解该表的内容,以便将该表转换为电子格式。据作者所知,这些问题都是新的。本文研究并实现了一种实现上述两种任务的算法。初步的实验结果表明,许多表格布局样式都具有令人满意的性能。
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来源期刊
模式识别与人工智能
模式识别与人工智能 Computer Science-Artificial Intelligence
CiteScore
1.60
自引率
0.00%
发文量
3316
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