Craquelure Classification of European Regional Paintings Using Convolutional Neural NetworkRobotics and Computer Science
- Sandra Crusa
"Abstract: Craquelure is the distinct patterns of cracks that form in painting. These cracks are determined by many factors, the most prevalent of these factors are the drying process, materials of the paint, and material to which the painting is applied. These factors are based on region and period. There are 4 distinct craquelure patterns from 4 European regions. These regions are Dutch, French, Flemish, and Italian. Convolutional Neural Networks (CNNs) are machine learning programs that are most notable applied to images. This is because of their unique convolutional layers. They have special techniques for processing images which make them optimal for image classification. This project applied a developed algorithm CNN to craquelure. A classification program that could tell the painting’s location of origin was desired. This was achieved, with a program that was at least 75% accurate and at times 90% accurate for determining the location of where a painting originated."