The HYPERDOC database is a publicly available hyperspectral imaging resource for the analysis of historical documents and mock-ups of inks and pigments. It consists of 1681 hyperspectral datacubes, containing millions of reflectance spectra, covering the VNIR (400–1000 nm) and SWIR (900–1700 nm) spectral ranges, including different ink recipes and documents from the 15th to 20th centuries, preserved in two archives in Granada, Spain. We will present the data acquisition process and structure of the database, followed by a live demonstration of its functionality, guiding participants through its use. Additionally, three applications of the database will be summarized, including document binarization, ink classification using machine learning techniques, and ink aging analysis. The HYPERDOC database facilitates the integration of advanced imaging techniques into document analysis and preservation, contributing to the non-invasive study of historical materials.
This research explores the application of image color analysis techniques to identify and classify historic photoreproductive processes—such as blueprinting, diazotype, and other early photographic reproduction methods—based on the color signatures they leave on architectural and technical drawings. The objective is to develop a systematic approach for automatically detecting the specific process used in the reproduction of these drawings, which is critical for preservation, restoration, and analysis in historical studies. Digital microscopy is employed to examine original 20th century photoreproductions from a historical technical company's archive in Greece. The processes examined are cyanotype, both positive and negative, diazotype of black and red color of line and Gel- lithography of black and brown lines. The visual features of photoreproductions are analyzed using computational pattern recognition techniques that emphasize the color of lines and type of printing process. The findings computational analysis are cross-referenced, and the resulting variables conclude the classification of prints, according to their colors. The results will contribute to the creation of an effective and accurate identification system for both photographic and photomechanical prints.