  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historical documents based on the physical materials of their writing surfaces.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.
