Back to articles
Proceedings Paper
Volume: 22 | Article ID: 34
Image
Digital Image Processing for Identification and Classification of Historic Photoreproductive Processes Used in Architectural and Technical Drawings based on Color Analysis
  DOI :  10.2352/issn.2168-3204.2025.22.1.34  Published OnlineJune 2025
Abstract
Abstract

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.

Subject Areas :
Views 0
Downloads 0
 articleview.views 0
 articleview.downloads 0
  Cite this article 

Manto Sotiropoulou, Vassiliki Kokla, "Digital Image Processing for Identification and Classification of Historic Photoreproductive Processes Used in Architectural and Technical Drawings based on Color Analysisin Archiving Conference,  2025,  pp 182 - 186,  https://doi.org/10.2352/issn.2168-3204.2025.22.1.34

 Copy citation
  Copyright statement 
Copyright ©2025 Society for Imaging Science and Technology 2025
archiving
Archiving Conference
2161-8798
2161-8798
Society for Imaging Science and Technology
IS&T 7003 Kilworth Lane, Springfield, VA 22151 USA