Surface Topography Used for Ink Detection on Herculaneum Papyri
Reading the Herculaneum papyri is challenging because both the scrolls and the ink, which is carbon-based, are carbonized. In X-ray radiography and tomography, ink detection typically relies on density- or composition-driven contrast, but carbon ink on carbonized papyrus provides little attenuation contrast. Building on earlier X-ray phase contrast tomographic and microscopic observations suggesting that relief contributes to letter visibility, we show that surface morphology
Researchers have developed a method using surface topography to detect ink on the carbonized Herculaneum papyri, where traditional X-ray methods struggle due to low contrast. By training a deep-learning model on three-dimensional optical profilometry data, inked and uninked areas can be distinguished. While bulk relief or universal roughness cues are not consistently present, high-resolution topography alone contains a usable signal for ink detection within the dataset. The study quantifies how lateral sampling affects learnability and model performance on different resolutions. This proof-of-concept demonstrates the potential for morphology-based reading of closed scrolls, informing future imaging resolution needs.
The application of deep learning to surface topography for ink detection on Herculaneum papyri offers a novel approach to deciphering ancient texts where traditional methods fail.
📌 Kaynak
Bu haber XML kaynağından derlenmiştir. Tamamı için orijinal habere gidin.
Orijinal haberi oku →