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首页> 外文期刊>IEEE transactions on information forensics and security >Exploring Character Shapes for Unsupervised Reconstruction of Strip-Shredded Text Documents
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Exploring Character Shapes for Unsupervised Reconstruction of Strip-Shredded Text Documents

机译：探索字符形状以无监督地重建带状文本文档

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摘要

Digital reconstruction of mechanically shredded documents has received increasing attention in the last years mainly for historical and forensics needs. Computational methods to solve this problem are highly desirable in order to mitigate the time-consuming human effort and to preserve document integrity. The reconstruction of strips-shredded documents is accomplished by horizontally splicing pieces so that the arising sequence (solution) is as similar as the original document. In this context, a central issue is the quantification of the fitting between the pieces (strips), which generally involves stating a function that associates a pair of strips to a real value indicating the fitting quality. This problem is also more challenging for text documents, such as business letters or legal documents, since they depict poor color information. The system proposed here addresses this issue by exploring character shapes as visual features for compatibility computation. Experiments conducted with real mechanically shredded documents showed that our approach outperformed in accuracy other popular techniques in the literature considering documents with (almost) only textual content.
机译：过去几年中，主要是出于历史和司法鉴定的需要，对机械粉碎文档的数字化重建越来越受到关注。为了减轻耗时的人力并保持文档完整性，非常需要用于解决该问题的计算方法。条状文档的重建是通过水平拼接来完成的，因此出现的顺序（解决方案）与原始文档相似。在这种情况下，一个中心问题是零件（条带）之间的拟合的量化，这通常涉及陈述将一对条带与指示拟合质量的实际值相关联的函数。对于文本文档（例如商务信函或法律文档）来说，此问题也更具挑战性，因为它们描述的色彩信息很差。本文提出的系统通过探索字符形状作为兼容性计算的视觉特征来解决此问题。使用真正的机械切碎文档进行的实验表明，考虑到（几乎）仅具有文本内容的文档，我们的方法在准确性方面优于其他流行的技术。

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