Non Algebraic Techniques for Digital Processing of Historic Painting Research Documentation Cover Image

Non Algebraic Techniques for Digital Processing of Historic Painting Research Documentation
Non Algebraic Techniques for Digital Processing of Historic Painting Research Documentation

Author(s): Magdelena Stoyanova, Diego C. Stoyanov, Lilia Pavlova
Subject(s): Museology & Heritage Studies, Library and Information Science, Cataloguing, Information Architecture, Preservation, Electronic information storage and retrieval
Published by: Институт по математика и информатика - Българска академия на науките
Keywords: Digital Image Procession; Non Algebraic Digital Techniques; Historic Painting Research Documentation

Summary/Abstract: Conservation of historic painting requires comprehensive and correct information to be analyzed during the diagnostic and decision making process in a systematic and rational approach. This paper aims to contribute for the setting of an optimal working process tailored for digital image processing of historic painting research documentation, to be used also in other interdisciplinary areas. To the end it integrates the purely algebraic approach with expediencies derived from the specific scientific background of multidimensional and multimodal images of different types (MMI). Following key tasks have been addressed: 1)Presentation involving non algebraic methods whose main advantages are the functionality to the objectives of the scientific study, the relatively reduced computational complexity and the possibility of parallel processing of MMI; 2) Simulation of new digital expedients based on developed methods by using test databases containing different types of MMIs; 3) MMI analysis based on non-algebraic intelligent segmentation methods that expand the possibilities for proper detection, recognition and evaluation of the changes in the surveyed objects; 4) MMI processing based on adaptive interpolation, which is of small computational complexity and provides high quality interpolated areas (objects) in 2,5D, facilitating the decision-making process on the basis of the relevant information. The effectiveness of the proposed approaches in terms of scientific functionality, accuracy of the diagnosis, and low computational complexity is demonstrated with examples of applications to typical real data in the respective subject area.

  • Issue Year: 2018
  • Issue No: VIII
  • Page Range: 121-132
  • Page Count: 12
  • Language: English