Date of Award
2013
Publication Type
Master Thesis
Degree Name
M.A.Sc.
Department
Electrical and Computer Engineering
Keywords
Communication and the arts, Applied sciences, Classification, Crack detector, Craquelure, K-nn, Lda, Morphology
Supervisor
Maev, Roman
Rights
info:eu-repo/semantics/openAccess
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Abstract
Craquelure represents the unique crack formations that form on a material with age. This thesis is specifically concerned with the craquelure patterns found on historical art paintings. Although the significance of craquelure has been noted for over 300 years, recent research has shown that these patterns are related to the materials and methods employed by the artist and that these clues may assist in the task of attribution. It has been shown that different art paintings constructed from the same geographical location exhibit similar craquelure formation patterns. With the intention of alleviating expertise on the subject of craquelure, the development of a framework for the geographical analysis of craquelure patterns has been attempted in literature. This thesis seeks to expand on these results with the intention of increasing the accuracy rate in the classification of craquelure to their corresponding geographical origins. Through the use of mathematical morphology and various image processing techniques, craquelure images were converted to binary images. Specific features were then extracted from the binary image and used in the classification process. Several different classifiers were tested and compared in this thesis.
Recommended Citation
El-Youssef, Mouhanned, "The extraction and classification of craquelure patterns for geographical analysis of fine art painting" (2013). Electronic Theses and Dissertations. 4973.
https://scholar.uwindsor.ca/etd/4973