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Similarity-based Image Retrieval for Revealing Forgery of Handwritten Corpora

机译:基于相似性的图像检索,用于揭示手写语料库的伪造

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Authorship attribution is a problem with a long history and a wide range of applications. Recent works in non-traditional authorship attribution contexts demonstrate the practicality of automatic analysis of documents based on authorial style. However, such analyses are difficult to apply and few "best practices" are available. In this paper, we show how quantitative techniques based on image similarity search can be profitably exploited for revealing forgery of handwritten corpora. More in details, we explore the case where a document is represented by means of the image of the document itself. Preliminary experimental results conducted on real data demonstrate the effectiveness of the proposed approach.
机译:作者归属是历史悠久的问题和广泛的应用程序。 非传统作者归因环境中的最新作品展示了基于授权风格的自动分析的实用性。 但是,这种分析难以申请,并且很少有“最佳实践”。 在本文中,我们展示了如何基于图像相似性搜索的定量技术如何利用用于揭示手写语料库的伪造。 更多详细信息,我们探索通过文档本身的图像表示文档的情况。 对实际数据进行的初步实验结果表明了所提出的方法的有效性。

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