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Keyword spotting in historical handwritten documents based on graph matching

机译:基于图形匹配的历史手写文档中的关键字发现

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In the last decades historical handwritten documents have become increasingly available in digital form. Yet, the accessibility to these documents with respect to browsing and searching remained limited as full automatic transcription is often not possible or not sufficiently accurate. This paper proposes a novel reliable approach for template-based keyword spotting in historical handwritten documents. In particular, our framework makes use of different graph representations for segmented word images and a sophisticated matching procedure. Moreover, we extend our method to a spotting ensemble. In an exhaustive experimental evaluation on four widely used benchmark datasets we show that the proposed approach is able to keep up or even outperform several state-of-the-art methods for template- and learning-based keyword spotting. (C) 2018 Elsevier Ltd. All rights reserved.
机译:在过去十年中,历史手写文件越来越多地以数字形式提供。 然而,对浏览和搜索的这些文档的可访问性仍然有限,因为通常不可能或不充分准确。 本文提出了一种新的基于模板的可靠方法,在历史手写文档中的基于模板的关键字斑点。 特别是,我们的框架利用不同的图形表示进行分段字图像和复杂的匹配过程。 此外,我们将我们的方法扩展到发现集合。 在四个广泛使用的基准数据集的详尽实验评估中,我们表明所提出的方法能够跟上甚至优于几种最先进的方法,用于基于模板和基于学习的关键字。 (c)2018年elestvier有限公司保留所有权利。

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