In this paper an attempt has been made to apply data mining techniques to the task of separation and categorization features in digital images of artworks. Both craquelure separation and retouching identification are important steps in art restoration process. Since the main goal is to enable recognition of character and cause of damage, as well as forecasting its further enlargement, a proper tool for precise detection of the pattern is needed. However, the complex nature of the pat- tern is a reason why a simple, universal detection algorithm is not always possible to implement. Algorithms presented in this work apply mining structures which depend of expandable set of attributes forming a feature vector, and thus offer an elastic structure for analysis. 1
['Joanna Gancarczyk']
Data Mining Approach to Digital Image Processing in Old Painting Restoration