论文标题
基于图像的古代历史文档的材料分析
Image-based material analysis of ancient historical documents
论文作者
论文摘要
研究人员不断进行佐证测试，以根据其写作表面的物理材料对古老的历史文档进行分类。但是，这些测试通常是在现场进行的，需要实际访问手稿对象。该程序涉及大量的时间和成本，并可能损害手稿。开发一种仅使用数字图像对此类文档进行分类的技术可能非常有用和有效。为了解决这个问题，本研究使用著名的历史收藏集《死海卷轴》的图像提出了一种新方法来对手稿的材料进行分类。所提出的分类器使用二维傅立叶变换来识别手稿表面中的模式。将使用转换与多数投票过程的二进制分类系统结合在一起，被证明对此分类任务有效。这项试点研究显示，从羊皮纸或纸莎草材料产生的限制手稿中，成功的分类百分比最高97％。基于傅立叶空间网格表示的特征向量优于同心傅立叶空间格式。
Researchers continually perform corroborative tests to classify ancient historical documents based on the physical materials of their writing surfaces. However, these tests, often performed on-site, requires actual access to the manuscript objects. The procedures involve a considerable amount of time and cost, and can damage the manuscripts. Developing a technique to classify such documents using only digital images can be very useful and efficient. In order to tackle this problem, this study uses images of a famous historical collection, the Dead Sea Scrolls, to propose a novel method to classify the materials of the manuscripts. The proposed classifier uses the two-dimensional Fourier Transform to identify patterns within the manuscript surfaces. Combining a binary classification system employing the transform with a majority voting process is shown to be effective for this classification task. This pilot study shows a successful classification percentage of up to 97% for a confined amount of manuscripts produced from either parchment or papyrus material. Feature vectors based on Fourier-space grid representation outperformed a concentric Fourier-space format.
