Ceramic sherds are the most common finds in archaeology. They are complex to analyze and onerous to process. A large number of indistinct sherds coming from excavations must be preliminarily grouped in some categories. This clusterization helps the next phase, in which archaeologists classify the ceramics. Due to the difficulty of these preliminary, repetitive, and routine phases, a great deal of archaeological material remains unstudied in museum repositories or archaeological sites. An effective method to automate these routine phases is presented in this article. The proposed method performs a shape feature segmentation of the sherds, which is fundamental to undertake any further analysis, such as potsherds classification, reconstruction, or cataloging. A set of specific shape features, useful to understand the find properties, is defined and methods for recognizing them are proposed. The method's performance is tested in the analysis of some real, critical cases.

中文翻译：

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陶瓷发现的自动形状特征识别

陶瓷碎片是考古学中最常见的发现。它们分析起来很复杂，处理起来也很繁琐。大量来自发掘的模糊碎片必须初步归类为某些类别。这种聚类有助于下一阶段，考古学家对陶瓷进行分类。由于这些初步、重复和常规阶段的难度，大量考古材料仍未在博物馆存储库或考古遗址中进行研究。本文介绍了一种使这些常规阶段自动化的有效方法。所提出的方法对陶片进行形状特征分割，这是进行任何进一步分析的基础，例如陶片分类、重建或编目。一组特定的形状特征，有助于理解查找属性，被定义并提出了识别它们的方法。该方法的性能在一些真实的关键案例的分析中进行了测试。