Improving Palimpsest Readability via Image Preprocessing: An Investigation into Adjustment Techniques

Abstract

The palimpsests represent unique historical sources that hold the potential for new insights in the field of human history. These manuscripts, rewritten and reused over time, pose challenges in the research related to their readability and interpretation. The present study aims to investigate the readability of palimpsests through the use of image preprocessing techniques. The article focuses on methods for the preprocessing of palimpsests that could lead to a significant improvement in the readability of the 'hidden' text. The challenges encountered during the processing of palimpsests are explored and various techniques applicable to improving the readability of these manuscripts are analyzed. The primary goal of preprocessing in this context is to separate the 'hidden' text from the visible one, neutralizing material defects and aging. The article presents specific methods such as extracting specific color range from a palimsest image. The experimental techniques are highlighted with sample codes illustrating the application of the respective technology. The current research attempts to advance the development of methods for processing palimpsests and opens up new perspectives for extracting information from those historically valuable manuscripts.

Keywords

• AI
• Palimpest
• Manuscript
• Image processing