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古希腊铭文的自动笔迹识别。

Automatic writer identification of ancient Greek inscriptions.

作者信息

Panagopoulos Michail, Papaodysseus Constantin, Rousopoulos Panayiotis, Dafi Dimitra, Tracy Stephen

机构信息

National Technical University of Athens, Athens, Greece.

出版信息

IEEE Trans Pattern Anal Mach Intell. 2009 Aug;31(8):1404-14. doi: 10.1109/TPAMI.2008.201.

Abstract

This paper introduces a novel methodology for the classification of ancient Greek inscriptions according to the writer who carved them. Inscription writer identification is crucial for dating the written content, which in turn is of fundamental importance in the sciences of history and archaeology. To achieve this, we first compute an ideal or "platonic" prototype for the letters of each inscription separately. Next, statistical criteria are introduced to reject the hypothesis that two inscriptions are carved by the same writer. In this way, we can determine the number of distinct writers who carved a given ensemble of inscriptions. Next, maximum likelihood considerations are employed to attribute all inscriptions in the collection to the respective writers. The method has been applied to 24 Ancient Athenian inscriptions and attributed these inscriptions to six different identified hands in full accordance with expert epigraphists' opinions.

摘要

本文介绍了一种根据雕刻者对古希腊铭文进行分类的新方法。铭文作者识别对于确定书写内容的年代至关重要,而这反过来在历史和考古学中具有根本重要性。为实现这一目标,我们首先分别为每个铭文的字母计算一个理想的或“柏拉图式”的原型。接下来,引入统计标准以拒绝两个铭文由同一作者雕刻的假设。通过这种方式,我们可以确定雕刻给定一组铭文的不同作者的数量。然后,采用最大似然性考量将集合中的所有铭文归属于各自的作者。该方法已应用于24篇古雅典铭文,并完全根据专家铭文学家的意见将这些铭文归属于六种不同的已知笔迹。

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