Image-based material analysis of ancient historical documents

• URL: http://arxiv.org/abs/2203.01042v1
• Date: Wed, 2 Mar 2022 11:39:22 GMT
• Title: Image-based material analysis of ancient historical documents
• Authors: Thomas Reynolds, Maruf A. Dhali, Lambert Schomaker
• Abstract summary: 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. 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.
• Score: 5.285396202883411
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Researchers continually perform corroborative tests to classify ancient historical documents based on the physical materials of their writing surfaces.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.

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