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Straight Line Reconstruction for Fully Materialized Table Extraction in Degraded Document Images

机译:直线重构用于在退化文档图像中完全物化表提取

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Tables are one of the best ways to synthesize information such as statistical results, key figures in documents. In this article we focus on the extraction of materialized tables in document images, in the particular case where acquisition noise can disrupt the recovering of the table structures. The sequential printings/scannings of a document and its deterioration can lead to 'broken' lines among the materialized segments of the tables. We propose a method based on the search for straight line segments in documents, relying on a new image transform that locally defines primitives well suited for pattern recognition and on a proposed theoretical model of lines in order to confirm their presence among a set of confident potential line parts. The extracted straight line segments are then used to reconstruct the table structures. Our approach has been evaluated both from quality and stability points of view.
机译:表格是综合信息(如统计结果,文档中的关键指标)的最佳方法之一。在本文中,我们重点介绍文档图像中物化表的提取,在特定情况下,采集噪声会破坏表结构的恢复。文档的连续打印/扫描及其变质会导致表格的物化部分之间出现“折断”线。我们提出了一种基于搜索文档中直线段的方法,该方法依赖于一种新的图像变换,该变换在本地定义了非常适合模式识别的图元,并提出了一种理论上的线模型,以确认线在一组有信心的潜力中的存在。线零件。然后,将提取的直线段用于重建表格结构。我们的方法已经从质量和稳定性的角度进行了评估。

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